Command keywords with input detection windowing

ABSTRACT

A device, such as Network Microphone Device or a playback device, receives an indication of a track change associated with a playback queue output by a media playback system. In response, an input detection window is opened for a given time period. During the given time period the device is arranged to receive an input sound data stream representing sound detected by a microphone. The input sound data stream is analyzed for a plurality of command keywords and/or a wake-word for a Voice Assistant Service (VAS) and, based on the analysis, it is determined that the input sound data stream includes voice input data comprising a command keyword or a wake-word for a VAS. In response, the device takes appropriate action such as causing the media playback system to perform a command corresponding to the command keyword or sending at least part of the input sound data stream to the VAS.

CROSS-REFERENCE TO RELATED APPLICATION

This application is a continuation of U.S. patent application Ser. No.16/879,549, filed May 20, 2020, which is incorporated herein byreference in its entirety.

FIELD OF THE DISCLOSURE

The present technology relates to consumer goods and, more particularly,to methods, systems, products, features, services, and other elementsdirected to voice-assisted control of media playback systems or someaspect thereof.

BACKGROUND

Options for accessing and listening to digital audio in an out-loudsetting were limited until in 2002, when SONOS, Inc. began developmentof a new type of playback system. Sonos then filed one of its firstpatent applications in 2003, entitled “Method for Synchronizing AudioPlayback between Multiple Networked Devices,” and began offering itsfirst media playback systems for sale in 2005. The Sonos Wireless HomeSound System enables people to experience music from many sources viaone or more networked playback devices. Through a software controlapplication installed on a controller (e.g., smartphone, tablet,computer, voice input device), one can play what she wants in any roomhaving a networked playback device. Media content (e.g., songs,podcasts, video sound) can be streamed to playback devices such thateach room with a playback device can play back corresponding differentmedia content. In addition, rooms can be grouped together forsynchronous playback of the same media content, and/or the same mediacontent can be heard in all rooms synchronously.

BRIEF DESCRIPTION OF THE DRAWINGS

Features, aspects, and advantages of the presently disclosed technologymay be better understood with regard to the following description,appended claims, and accompanying drawings, as listed below. A personskilled in the relevant art will understand that the features shown inthe drawings are for purposes of illustrations, and variations,including different and/or additional features and arrangements thereof,are possible.

FIG. 1A is a partial cutaway view of an environment having a mediaplayback system configured in accordance with aspects of the disclosedtechnology.

FIG. 1B is a schematic diagram of the media playback system of FIG. 1Aand one or more networks.

FIG. 2A is a functional block diagram of an example playback device.

FIG. 2B is an isometric diagram of an example housing of the playbackdevice of FIG. 2A.

FIG. 2C is a diagram of an example voice input.

FIG. 2D is a graph depicting an example sound specimen in accordancewith aspects of the disclosure.

FIGS. 3A, 3B, 3C, 3D and 3E are diagrams showing example playback deviceconfigurations in accordance with aspects of the disclosure.

FIG. 4 is a functional block diagram of an example controller device inaccordance with aspects of the disclosure.

FIGS. 5A and 5B are controller interfaces in accordance with aspects ofthe disclosure.

FIG. 6 is a message flow diagram of a media playback system.

FIG. 7A is a functional block diagram of certain components of a firstexample network microphone device in accordance with aspects of thedisclosure;

FIG. 7B is a functional block diagram of certain components of a secondexample network microphone device in accordance with aspects of thedisclosure;

FIG. 7C is a functional block diagram illustrating an example statemachine in accordance with aspects of the disclosure;

FIG. 8 is a flow diagram of an example method to perform an operationbased on a voice input data stream received within an input detectionwindow; and

FIGS. 9A, 9B, 9C and 9D are graphs showing an exemplary analysis fordetermining an input detection window.

The drawings are for purposes of illustrating example embodiments, butit should be understood that the inventions are not limited to thearrangements and instrumentality shown in the drawings. In the drawings,identical reference numbers identify at least generally similarelements.

DETAILED DESCRIPTION I. Overview

Example techniques described herein involve wake-word engines configuredto detect commands. An example network microphone device (“NMD”) mayimplement such a wake-word engine in parallel with a wake-word enginethat invokes a voice assistant service (“VAS”). While a VAS wake-wordengine may be involved with nonce wake-words, such as wake-words that donot have any particular meaning in themselves, a command keyword engineis invoked with commands, such as “play” or “skip.”

Network microphone devices may be used facilitate voice control of smarthome devices, such as wireless audio playback devices, illuminationdevices, appliances, and home-automation devices (e.g., thermostats,door locks, etc.). An NMD is a networked computing device that typicallyincludes an arrangement of microphones, such as a microphone array, thatis configured to detect sound present in the NMD's environment. In someexamples, an NMD may be implemented within another device, such as anaudio playback device.

A voice input to such an NMD will typically include a wake word followedby an utterance comprising a user request. In practice, a wake word istypically a predetermined nonce word or phrase used to “wake up” an NMDand cause it to invoke a particular voice assistant service (“VAS”) tointerpret the intent of voice input in detected sound. For example, auser might speak the wake word “Alexa” to invoke the AMAZON® VAS, “Ok,Google” to invoke the GOOGLE® VAS, “Hey, Siri” to invoke the APPLE® VAS,or “Hey, Sonos” to invoke a VAS offered by SONOS®, among other examples.In practice, a wake word may also be referred to as, for example, anactivation-, trigger-, wakeup-word or -phrase, and may take the form ofany suitable word, combination of words (e.g., a particular phrase),and/or some other audio cue.

To identify whether sound detected by the NMD contains a voice inputthat includes a particular wake word, NMDs often utilize a wake-wordengine, which is typically onboard the NMD. The wake-word engine may beconfigured to identify (i.e., “spot” or “detect”) a particular wake wordin recorded audio using one or more identification algorithms. Suchidentification algorithms may include pattern recognition trained todetect the frequency and/or time domain patterns that speaking the wakeword creates. This wake-word identification process is commonly referredto as “keyword spotting.” In practice, to help facilitate keywordspotting, the NMD may buffer sound detected by a microphone of the NMDand then use the wake-word engine to process that buffered sound todetermine whether a wake word is present in the recorded audio.

When a wake-word engine detects a wake word in recorded audio, the NMDmay determine that a wake-word event (i.e., a “wake-word trigger”) hasoccurred, which indicates that the NMD has detected sound that includesa potential voice input. The occurrence of the wake-word event typicallycauses the NMD to perform additional processes involving the detectedsound. With a VAS wake-word engine, these additional processes mayinclude extracting detected-sound data from a buffer, among otherpossible additional processes, such as outputting an alert (e.g., anaudible chime and/or a light indicator) indicating that a wake word hasbeen identified. Extracting the detected sound may include reading outand packaging a stream of the detected-sound according to a particularformat and transmitting the packaged sound-data to an appropriate VASfor interpretation.

In turn, the VAS corresponding to the wake word that was identified bythe wake-word engine receives the transmitted sound data from the NMDover a communication network. A VAS traditionally takes the form of aremote service implemented using one or more cloud servers configured toprocess voice inputs (e.g., AMAZON's ALEXA, APPLE's SIRI, MICROSOFT'sCORTANA, GOOGLE'S ASSISTANT, etc.). In some instances, certaincomponents and functionality of the VAS may be distributed across localand remote devices.

When a VAS receives detected-sound data, the VAS processes this data,which involves identifying the voice input and determining an intent ofwords captured in the voice input. The VAS may then provide a responseback to the NMD with some instruction according to the determinedintent. Based on that instruction, the NMD may cause one or more smartdevices to perform an action. For example, in accordance with aninstruction from a VAS, an NMD may cause a playback device to play aparticular song or an illumination device to turn on/off, among otherexamples. In some cases, an NMD, or a media system with NMDs (e.g., amedia playback system with NMD-equipped playback devices) may beconfigured to interact with multiple VASes. In practice, the NMD mayselect one VAS over another based on the particular wake word identifiedin the sound detected by the NMD.

One challenge with traditional wake-word engines is that they can beprone to false positives caused by “false wake word” triggers. A falsepositive in the NMD context generally refers to detected sound inputthat erroneously invokes a VAS. With a VAS wake-work engine, a falsepositive may invoke the VAS, even though there is no user actuallyintending to speak a wake word to the NMD.

For example, a false positive can occur when a wake-word engineidentifies a wake word in detected sound from audio (e.g., music, apodcast, etc.) playing in the environment of the NMD. This output audiomay be playing from a playback device in the vicinity of the NMD or bythe NMD itself. For instance, when the audio of a commercial advertisingAMAZON's ALEXA service is output in the vicinity of the NMD, the word“Alexa” in the commercial may trigger a false positive. A word or phrasein output audio that causes a false positive may be referred to hereinas a “false wake word.”

In other examples, words that are phonetically similar to an actual wakeword cause false positives. For example, when the audio of a commercialadvertising LEXUS® automobiles is output in the vicinity of the NMD, theword “Lexus” may be a false wake word that causes a false positivebecause this word is phonetically similar to “Alexa.” As other examples,false positives may occur when a person speaks a VAS wake word or aphonetically similar word in a conversation.

The occurrences of false positives are undesirable, as they may causethe NMD to consume additional resources or interrupt audio playback,among other possible negative consequences. Some NMDs may avoid falsepositives by requiring a button press to invoke the VAS, such as on theAMAZON FIRETV remote or the APPLE TV remote.

In contrast to a pre-determined nonce wake word that invokes a VAS, akeyword that invokes a command (referred to herein as a “commandkeyword”) may be a word or a combination of words (e.g., a phrase) thatfunctions as a command itself, such as a playback command. In someimplementations, a command keyword may function as both a wake word andthe command itself. That is, when a command keyword engine detects acommand keyword in recorded audio, the NMD may determine that a commandkeyword event has occurred and responsively perform a commandcorresponding to the detected keyword. For instance, based on detectingthe command keyword “pause,” the NMD causes playback to be paused. Oneadvantage of a command keyword engine is that the recorded audio doesnot necessarily need to be sent to a VAS for processing, which mayresult in a quicker response to the voice input as well as increaseduser privacy, among other possible benefits. In some implementationsdescribed below, a detected command keyword event may cause one or moresubsequent actions, such as local natural language processing of a voiceinput. In some implementations, a command keyword event may be onecondition among one or more other conditions that must be detectedbefore causing such actions.

According to example techniques described herein, a command keyword islistened for and detected during a given time window, time period,listening window or input detection window. The given time period may bepredetermined, set via a controller device, set on setup of a mediaplayback system or playback device, or adaptive as a media playbacksystem or playback device is used.

The time period may be triggered by a certain event or condition, suchas reaching the end of a media item or track being played. This mayreduce false positives. For example, when a new audio track beginsplaying, it is more likely that a user will wish to interact with thesystem at this time. Accordingly, an activation window may be opened fora predetermined time period around the changing of a track or mediaitem, enabling command keywords to be received by the NMD, instead ofcontinually listening for command keywords. This enables commandkeywords to be received and command keyword events to be generatedduring the given time period without the need to continually listen forthe command keyword and possibly without relying on wake word eventgeneration or user interaction to initiate the listening for a commandkeyword.

In some examples, one or more wake-word detections remain invokableduring the listening window in addition to directly acting on a commandkeyword. In other words, a voice assistant can still be invoked duringthe listening window by preceding a command with a wakeword. Thelistening window may be applied to listening for interactions with avoice assistant, so that outside the listening window, the NMD is notlistening for voice assistant wakewords, which may further reduce falsepositives and/or improve privacy. Some examples may listen for voiceassistant wakewords but not command keywords outside the listeningwindow, so that a voice assistant remains continually available andfalse positives associated with command keywords, which may be subjectto a lower level of processing than voice assistant utterances, isreduced. In still other examples, during the listening window a voiceassistant wakeword detector is disabled and only command keywords arelistened for, or some but not all voice assistant wakeword detectors aredisabled during the listening window. This may allow local processingresources to be used most effectively during the listening window.

According to example techniques described herein, after detecting acommand keyword, example NMDs may generate a command keyword event (andperform a command corresponding to the detected command keyword) onlywhen certain conditions corresponding to the detected command keywordare met. For instance, after detecting the command keyword “skip,” anexample NMD generates a command keyword event (and skips to the nexttrack) only when certain playback conditions indicating that a skipshould be performed are met. These playback conditions may include, forexample, (i) a first condition that a media item is being played back,(ii) a second condition that a queue is active, and (iii) a thirdcondition that the queue includes a media item subsequent to the mediaitem being played back. If any of these conditions are not satisfied,the command keyword event is not generated (and no skip is performed).

When command keywords and/or VAS wake-words are detected during a giventime period, privacy may also be improved because a device need not becontinually listening. This can be especially beneficial forfalse-positives which are identified in the VAS processing, after thewake-word engine has sent data to the VAS for processing. While from auser perspective no false positive behavior is noticed, a recording maystill be generated and stored by the VAS system, potentially on a cloudsystem or service outside of the user's control. Consider an NMDassociated with a playback device or system which is currently inactive.Such devices tend to be continually listening, and may react to afalse-positive wake-word in general conversation, as discussed above.This may involve storing a recording and/or sending data to a remote VASserver. While the VAS may partially mitigate the false-positive byrecognizing it and taking no action, so that a user might not evennotice that the false-positive occurred, data has neverthelesspotentially been transmitted and/or stored which can reduce the privacyof a user.

For example, by requiring both (a) detection of a command keyword and(b) certain conditions corresponding to the detected command keywordbefore generating a command keyword event, the prevalence of falsepositives may be reduced. For instance, when playing TV audio, dialogueor other TV audio would not have the potential to generate falsepositives for the “skip” command keyword since the TV audio input isactive (and not a queue).

Aspects of conditioning keyword events may also be applicable to VASwake-word engines and other traditional nonce wake-word engines. Forexample, such conditioning can possibly make practicable other wake wordengines in addition to command keyword engines that might otherwise beprone to false positives. For instance, an NMD may include a streamingaudio service wake word engine that supports certain wake words uniqueto the streaming audio service. For instance, after detecting astreaming audio service wake word, an example NMD generates a streamingaudio service wake word event only when certain streaming audio serviceare met. These playback conditions may include, for example, (i) anactive subscription to the streaming audio service and (ii) audio tracksfrom the streaming audio service in a queue, among other examples.

Further, a command keyword may be a single word or a phrase. Phrasesgenerally include more syllables, which generally make the commandkeyword more unique and easier to identify by the command keywordengine. Accordingly, in some cases, command keywords that are phrasesmay be less prone to false positive detections. Further, using a phrasemay allow more intent to be incorporated into the command keyword. Forinstance, a command keyword of “skip forward” signals that a skip shouldbe forward in a queue to a subsequent track, rather than backward to aprevious track.

Yet further, an NMD may include a local natural language unit (NLU). Incontrast to an NLU implemented in one or more cloud servers that arecapable of recognizing a wide variety of voice inputs, example localNLUs are capable of recognizing a relatively small library of keywords(e.g., 10,000 words and phrases), which facilitates practicalimplementation on the NMD. When the command keyword engine generates acommand keyword event after detecting a command keyword in a voiceinput, the local NLU may process a voice utterance portion of the voiceinput to look for keywords from the library and determine an intent fromthe found keywords.

If the voice utterance portion of the voice input includes at least onekeyword from the library, the NMD may perform the command correspondingto the command keyword according to one or more parameters correspondingto the least one keyword. In other words, the keywords may alter orcustomize the command corresponding to the command keyword. Forinstance, the command keyword engine may be configured to detect “play”as a command keyword and the local NLU library could include the phrase“low volume.” Then, if the user speaks “Play music at low volume” as avoice input, the command keyword engine generates a command keywordevent for “play” and uses the keyword “low volume” as a parameter forthe “play” command. Accordingly, the NMD not only causes playback basedon this voice input, but also lowers the volume.

Example techniques involve customizing the keywords in the library tousers of the media playback system. For instance, the NMD may populatethe library using names (e.g., zone names, smart device names, and usernames) that have been configured in the media playback system.Furthermore, the NMD may populate the local NLU library with names offavorite playlists, Internet radio stations, and the like. Suchcustomization allows the local NLU to more efficiently assist the userwith voice commands. Such customization may also be advantageous becausethe size of the local NLU library can be limited.

One possible advantage of a local NLU is increased privacy. Byprocessing voice utterances locally, a user may avoid transmitting voicerecordings to the cloud (e.g., to servers of a voice assistant service).Further, in some implementations, the NMD may use a local area networkto discover playback devices and/or smart devices connected to thenetwork, which may avoid providing this data to the cloud. Also, theuser's preferences and customizations may remain local to the NMD(s) inthe household, perhaps only using the cloud as an optional backup. Otheradvantages are possible as well.

A first example implementation involves a device forming part of a mediaplayback system, including one or more processors, at least onemicrophone configured to detect sound, at least one speaker, and datastorage. The device determines a media item or track change associatedwith a playback queue output by the media playback system, andresponsive to the media item or track change opens an input detectionwindow for a given time period or duration during which an input sounddata stream is received from the at least one microphone. The inputsound data stream represents sound detected by the at least onemicrophone and is analyzed by the at least one processor for a pluralityof command keywords supported by the device. The playback commandkeywords may be detected by a command keyword engine associated with thedevice. Based on the analysis of the command keyword it is determinedwhether the input sound data stream includes voice input data comprisinga command keyword, wherein the command keyword is one of the pluralityof command keywords supported by the playback device, and in responsecauses the media playback system to perform a command corresponding tothe command keyword.

The device may be a playback device comprising at least one speaker foroutputting sound data, such as media obtained from a local library or amedia content service such as SPOTIFY, PANDORA, AMAZON MUSIC, or APPLEMUSIC. Alternatively, the device may be an NMD capable of receivingvoice input data, processing it and transmitting one or more commands toanother device, such as a playback device, which forms part of the mediaplayback system.

The opening of an input detection window for a given time period mayreduce the resource requirements for operating such a system. Componentsof the system required for natural language processing, such as the atleast one microphone and a voice recognition component associated withthe at least one process, as will be described below, areresource-intensive. Therefore, by allowing voice input to be detectedand processed during an input detection window, the amount of time suchresource-intensive components are active may be reduced. This isbeneficial for portable devices which rely on battery power and moregenerally in reducing power requirements for all devices, for example bylowering a stand-by or idle power draw in a playback device which is notreproducing media. Furthermore, by detecting and processing voice inputduring an input detection window privacy for users is also increased ifthe system is not continuously monitoring received sound.

Opening an input detection window when an indication of a media item ortrack change is determined enables voice input to be detected andprocessed when the likelihood of receiving such input is high. Examplesof such indications or predicted indications include changes in themedia content being output. For example, when it is known that a mediaitem change is coming—that is, a current media item being reproduced isapproaching an end—it can be determined that a media item or trackchange is imminent and as such, the input detection window may be openeda predetermined time before the track change happens to anticipatepotential user voice commands being received. For example, many mediaitems may have an identifiable ending portion, such as a fade out, wherea command is more likely to be provided to the playback device.

A length of the input detection window may be variable and can bedetermined based on user data as will be described below. Furthermore,the length of the input detection window may be static or dynamic. Astatic input detection window may have a predetermined length whichmight be set by a provider of the device or VAS or defined by a user ina setting or configuration data. A dynamic input detection window may beadjusted to reflect an actual use of the device or a given user's actualinteraction with the device, as will be discussed in more detail below.In addition to being static or dynamic, the length of the inputdetection window may also be based on the type of indications detectedand/or predicted.

Some examples will transmit the input sound data received to a cloudservice for further processing, and the input detection window may thenbe used to limit the interaction with a VAS. As such, wake-wordinteractions which require communication with a VAS, may be limited tothe input detection window, potentially reducing the resourcerequirements, reducing false-positive data sent to the VAS and improvingprivacy. A reduction in false-positives may also have an impact on VASresources because the volume of data sent to the VAS will be reduced asthe false-positives are reduced.

The device may comprise an internal library of command keywords whichare capable of being detected and capable of generating associatedcommand keyword events. Such command keywords may be associated with aplurality of different commands including configuration commands, suchas joining one or more zones of a media playback system together toreproduce media in synchrony, and control commands, such as controllingplayback of media items. A subset of the command keywords may beplayback command keywords which relate to the reproduction of media.Playback command keywords include play, pause, skip between media items(forward or back), repeat, scrubbing within a media item (forward orback), searching within a media item (such as forward or back by apredetermined time period, e.g. 30 seconds, or to a specified timewithin a media item), volume change, mute and stop. These commandkeywords may be detected and processed to generate correspondingplayback command events during the input detection window, enablinginteraction with the media playback system without the requirement toinitiate a VAS using a wake word. This may reduce latency because thereis no need to await results from a VAS.

Numerous events, some of which have been described above, may indicate achange of media item or track associated with a playback queue output bythe media playback system. For example, the playback device itself maymonitor an end time of a current media item or may receive aninstruction from another device indicating a change to the current mediaitem, such as skip command from a controller device.

A length of the input detection window may be adjusted according tocharacteristics of the track change, such as a type or category of acurrent media item, with different lengths from the end of a podcastthan from the end of a music track. Likewise the underlying cause of thetrack change may change the length, with a change of track moving to anext item in a playback queue having a different length than a trackchange initiated by a received command from a controller.

A length of the input detection window may be longer after a last orfinal media item in a playlist then after preceding media items. Thismay be useful because an end of a playlist may be less noticeable than achange from one media item to another so allowing more time fordetection is beneficial. For example, a volume change from one mediaitem to another may be easier to notice than a silence at the end of aplaylist. It may also be difficult to distinguish silence from a quietmedia item at low volume. Although the window is longer in this case,the overall impact on processing required and privacy is small becauseit applies only to the final media item in a playlist and not thepreceding items. Alternatively, or additionally, after a last or finalmedia item in a playlist, the device may default to listening for a VASwake word.

The device may store historical data in the data storage. The historicaldata includes data associated with past indications and associatedcommands. For example, an associated command may be a command which isreceived and an associated length of time between the command andassociated track change. The historical data may then be analyzed toadjust the given time period associated with the input detection window.This allows the length of the input detection window to be adjustedbased on previous user interactions.

When analyzing the historical data, a frequency of the associatedplayback commands and a time period, relative to a time of theindication that a track change is going to or has occurred, during whichthe associated playback commands were received by the media playbacksystem may be determined, and the given time period set according tothat frequency. This enables the time period that the input detectionwindow is open for to be based on usage data associated with the mediaplayback system, for example, how quickly and how often user actionswere received previously when a similar indication was detected. Forexample, the analysis may be based on assuming a normal distribution ofthe commands received, determining the mean and standard deviation fromthe historical data, setting a center of the input window as the mean,setting a start time of the input window as a first predetermined factorof the standard deviation before the mean, and setting an end time ofthe input window as a second predetermined factor of the standarddeviation after the mean. The first and second factor may be the same ordifferent and may be fractions or integers. In one example, the firstand second factor both equal 1. It will be appreciated that otherstatistical distributions can be used as well as the normaldistribution. In other examples, at least one of the open time, end timeand duration of the input window may be based on thresholds, for examplean end time may be set as when greater than or equal to 60%, 70%, 80% or90% of the commands have been received following the track change.

Some examples may consider a maximum time period or duration for theinput window, such as 30 seconds or 1 minute. This can help to maintainrelatively short windows for improved privacy and reduced falsepositives and resource requirements. Where a maximum duration is reachedthe window may be centered on mean value which, assuming a normaldistribution, can help to maximize the probability of receiving a usercommand in the window. Other examples may set a fixed time period orduration for the input window and center it on a mean value of thehistorical data. The maximum time periods and/or durations may be storedlocally on the playback device or within the playback system, or may bestored in cloud storage associated with a user account or the playbacksystem. The user may indicate a preference as to whether the timeperiod/duration information is stored locally or within the cloud.Optionally, when uploading to a cloud service the information may beanonymized to increase privacy.

In some examples, the given time period is associated with a useraccount of the media playback system enabling the time period to becustomized according to a particular account. To facilitate this, thehistorical data may also include data of respective user accountsassociated with the commands. This may allow the experience of eachindividual user to be customized, enabling multiple users of the samesystem to have their own respective input window time periods rather alluser interaction with the media playback system being considered as awhole. Where the user account is also used with other media playbacksystems, it can allow the given time period to be shared acrossdifferent systems. In yet further examples, the user account may be usedto store preferences of a minimum and/or maximum time period for theinput detection window to enhance privacy or improve recognition ofcommands. Furthermore, the user account may be used to store a voiceprofile of the user which can be used by the device to determine whichuser is providing the input voice data automatically and adjust thegiven time period accordingly.

Outside the input detection window, the input sound data stream may notbe analyzed. This ensures that privacy is maintained, and thatresource-intensive components of the device are not operable therebyincreasing the efficiency of the device.

The device may comprise a network interface, and the data storage maycomprise instructions which cause the transmission, via the networkinterface, of at least part of the input sound data to an externaldevice for analysis during the input detection window. The externaldevice may be a remote server. Data including a command may then bereceived from the external device which represents commands supported bythe device, which are then used to cause the media playback to performthe command. As mentioned above this enables the input sound data streamto be analyzed by an external device such as a VAS to enable othercommands to be actioned, such as commands which are not present in alocal library associated with the local command analysis unit. The dataprovided to the external device may include other information such astrack details, or device identifiers. Furthermore, the input sound datastream may be first analyzed to determine which portions are unable tobe processed locally, only those sections may then be sent to theexternal device for further processing. It will be appreciated that theexternal device may be on the same local area network as the device. Forexample, the media playback system may comprise a device which functionsas a VAS for the playback system. Alternatively, or additionally, theexternal device may be provided as part of a controller applicationrunning on a controller device. Controller applications may be run ondevices with relatively more computing power than a media playbackdevice.

Analyzing the input data stream may comprise determining a playbackcommand keyword using at least one of natural language processing todetermine intent based on an analysis of the playback command, andpattern matching based on a predefined library of keywords associatedwith playback command keywords. In some examples, a decision whether touse natural language processing, pattern matching, or both naturallanguage processing and pattern matching may be based on properties ofthe device and/or where the input data stream will be processed. Exampledevice properties include available processing resources and availablememory resources. Examples of where the input data stream will beprocessed include by the device itself or by a VAS external to thedevice.

A second example implementation involves a method to be performed by adevice in which a media item or track change associated with a mediaplayback system is determined and, responsive to the media item or trackchange, an input detection window is opened for a given time period.During the given time period an input sound data stream, representingsound detected by at least one microphone, is received and analyzed fora plurality of command keywords supported by the playback device. Basedon the analysis it is determined that the input sound data streamincludes voice data comprising a command keyword which is one of theplurality of command keywords supported by the playback device. Inresponse to the determination, the media playback system performs acommand corresponding to the command keyword.

A third example implementation involves a non-transitorycomputer-readable medium having instructions stored thereon that areexecutable by one or more processors to cause a device to performfunctions, and the device comprising at least one microphone configuredto detect sound. The functions comprise determining a media item ortrack change associated with a media playback system and, responsive tothe media item or track change, opening an input detection window for agiven time period. During the given time period an input sound datastream, representing sound detected by at least one microphone isreceived and analyzed for a plurality of command keywords supported bythe playback device. Based on the analysis it is determined that theinput sound data stream includes voice data comprising a command keywordwhich is one of the plurality of command keywords supported by theplayback device. In response to the determination, the media playbacksystem performs a command corresponding to the command keyword.

It will be appreciated that the second and third example implementationscan also use the features discussed above for the first exampleimplementation.

While some embodiments described herein may refer to functions performedby given actors, such as “users” and/or other entities, it should beunderstood that this description is for purposes of explanation only.The claims should not be interpreted to require action by any suchexample actor unless explicitly required by the language of the claimsthemselves.

Moreover, some functions are described herein as being performed “basedon” or “in response to” another element or function. “Based on” shouldbe understood that one element or function is related to anotherfunction or element. “In response to” should be understood that oneelement or function is a necessary result of another function orelement. For the sake of brevity, functions are generally described asbeing based on another function when a functional link exists; however,such disclosure should be understood as disclosing either type offunctional relationship.

II. Example Operation Environment

FIGS. 1A and 1B illustrate an example configuration of a media playbacksystem 100 (or “MPS 100”) in which one or more embodiments disclosedherein may be implemented. Referring first to FIG. 1A, the MPS 100 asshown is associated with an example home environment having a pluralityof rooms and spaces, which may be collectively referred to as a “homeenvironment,” “smart home,” or “environment 101.” The environment 101comprises a household having several rooms, spaces, and/or playbackzones, including a master bathroom 101 a, a master bedroom 101 b,(referred to herein as “Nick's Room”), a second bedroom 101 c, a familyroom or den 101 d, an office 101 e, a living room 101 f, a dining room101 g, a kitchen 101 h, and an outdoor patio 101 i. While certainembodiments and examples are described below in the context of a homeenvironment, the technologies described herein may be implemented inother types of environments. In some embodiments, for example, the MPS100 can be implemented in one or more commercial settings (e.g., arestaurant, mall, airport, hotel, a retail or other store), one or morevehicles (e.g., a sports utility vehicle, bus, car, a ship, a boat, anairplane), multiple environments (e.g., a combination of home andvehicle environments), and/or another suitable environment wheremulti-zone audio may be desirable.

Within these rooms and spaces, the MPS 100 includes one or morecomputing devices. Referring to FIGS. 1A and 1B together, such computingdevices can include playback devices 102 (identified individually asplayback devices 102 a-102 o), network microphone devices 103(identified individually as “NMDs” 103 a-102 i), and controller devices104 a and 104 b (collectively “controller devices 104”). Referring toFIG. 1B, the home environment may include additional and/or othercomputing devices, including local network devices, such as one or moresmart illumination devices 108 (FIG. 1B), a smart thermostat 110, and alocal computing device 105 (FIG. 1A). In embodiments described below,one or more of the various playback devices 102 may be configured asportable playback devices, while others may be configured as stationaryplayback devices. For example, the headphones 102 o (FIG. 1B) are aportable playback device, while the playback device 102 d on thebookcase may be a stationary device. As another example, the playbackdevice 102 c on the Patio may be a battery-powered device, which mayallow it to be transported to various areas within the environment 101,and outside of the environment 101, when it is not plugged into a walloutlet or the like.

With reference still to FIG. 1B, the various playback, networkmicrophone, and controller devices 102, 103, and 104 and/or othernetwork devices of the MPS 100 may be coupled to one another viapoint-to-point connections and/or over other connections, which may bewired and/or wireless, via a network 111, such as a LAN including anetwork router 109. For example, the playback device 102 j in the Den101 d (FIG. 1A), which may be designated as the “Left” device, may havea point-to-point connection with the playback device 102 a, which isalso in the Den 101 d and may be designated as the “Right” device. In arelated embodiment, the Left playback device 102 j may communicate withother network devices, such as the playback device 102 b, which may bedesignated as the “Front” device, via a point-to-point connection and/orother connections via the NETWORK 111.

As further shown in FIG. 1B, the MPS 100 may be coupled to one or moreremote computing devices 106 via a wide area network (“WAN”) 107. Insome embodiments, each remote computing device 106 may take the form ofone or more cloud servers. The remote computing devices 106 may beconfigured to interact with computing devices in the environment 101 invarious ways. For example, the remote computing devices 106 may beconfigured to facilitate streaming and/or controlling playback of mediacontent, such as audio, in the home environment 101.

In some implementations, the various playback devices, NMDs, and/orcontroller devices 102-104 may be communicatively coupled to at leastone remote computing device associated with a VAS and at least oneremote computing device associated with a media content service (“MCS”).For instance, in the illustrated example of FIG. 1B, remote computingdevices 106 are associated with a VAS 190 and remote computing devices106 b are associated with an MCS 192. Although only a single VAS 190 anda single MCS 192 are shown in the example of FIG. 1B for purposes ofclarity, the MPS 100 may be coupled to multiple, different VASes and/orMCSes. In some implementations, VASes may be operated by one or more ofAMAZON, GOOGLE, APPLE, MICROSOFT, SONOS or other voice assistantproviders. In some implementations, MCSes may be operated by one or moreof SPOTIFY, PANDORA, AMAZON MUSIC, or other media content services.

As further shown in FIG. 1B, the remote computing devices 106 furtherinclude remote computing device 106 c configured to perform certainoperations, such as remotely facilitating media playback functions,managing device and system status information, directing communicationsbetween the devices of the MPS 100 and one or multiple VASes and/orMCSes, among other operations. In one example, the remote computingdevices 106 c provide cloud servers for one or more SONOS Wireless HiFiSystems.

In various implementations, one or more of the playback devices 102 maytake the form of or include an on-board (e.g., integrated) networkmicrophone device. For example, the playback devices 102 a—e include orare otherwise equipped with corresponding NMDs 103 a—e, respectively. Aplayback device that includes or is equipped with an NMD may be referredto herein interchangeably as a playback device or an NMD unlessindicated otherwise in the description. In some cases, one or more ofthe NMDs 103 may be a stand-alone device. For example, the NMDs 103 fand 103 g may be stand-alone devices. A stand-alone NMD may omitcomponents and/or functionality that is typically included in a playbackdevice, such as a speaker or related electronics. For instance, in suchcases, a stand-alone NMD may not produce audio output or may producelimited audio output (e.g., relatively low-quality audio output).Similarly, the stand-alone playback device 102 a—e may interpret anyvoice commands using an in-built processor and/or natural languagemodule, thereby enabling the input voice data to be processed locally,and removing the need to transmit input voice data to a remote serverfor processing by a VAS.

The various playback and network microphone devices 102 and 103 of theMPS 100 may each be associated with a unique name, which may be assignedto the respective devices by a user, such as during setup of one or moreof these devices. For instance, as shown in the illustrated example ofFIG. 1B, a user may assign the name “Bookcase” to playback device 102 dbecause it is physically situated on a bookcase. Similarly, the NMD 103f may be assigned the named “Island” because it is physically situatedon an island countertop in the Kitchen 101 h (FIG. 1A). Some playbackdevices may be assigned names according to a zone or room, such as theplayback devices 102 e, 102 l, 102 m, and 102 n, which are named“Bedroom,” “Dining Room,” “Living Room,” and “Office,” respectively.Further, certain playback devices may have functionally descriptivenames. For example, the playback devices 102 a and 102 b are assignedthe names “Right” and “Front,” respectively, because these two devicesare configured to provide specific audio channels during media playbackin the zone of the Den 101 d (FIG. 1A). The playback device 102 c in thePatio may be named portable because it is battery-powered and/or readilytransportable to different areas of the environment 101. Other namingconventions are possible.

As discussed above, an NMD may detect and process sound from itsenvironment, such as sound that includes background noise mixed withspeech spoken by a person in the NMD's vicinity. For example, as soundsare detected by the NMD in the environment, the NMD may process thedetected sound to determine if the sound includes speech that containsvoice input intended for the NMD and ultimately a particular VAS. Forexample, the NMD may identify whether speech includes a wake wordassociated with a particular VAS.

In the illustrated example of FIG. 1B, the NMDs 103 are configured tointeract with the VAS 190 over a network via the network 111 and therouter 109. It will be appreciated that in other examples the NMDs 103are configured to process the detected sounds without interacting withthe VAS 190 over a network. Interactions with the VAS 190 may beinitiated, for example, when an NMD identifies in the detected sound apotential wake word, alternatively, interactions may be initiated basedon the detection of a command keyword in a given time period associatedwith a determined track or media item change. The identification causesa wake-word event, which in turn causes the NMD to begin transmittingdetected-sound data to the VAS 190. In some implementations, the variouslocal network devices 102-105 (FIG. 1A) and/or remote computing devices106 c of the MPS 100 may exchange various feedback, information,instructions, and/or related data with the remote computing devicesassociated with the selected VAS. Such exchanges may be related to orindependent of transmitted messages containing voice inputs. In someembodiments, the remote computing device(s) and the MPS 100 may exchangedata via communication paths as described herein and/or using a metadataexchange channel as described in U.S. application Ser. No. 15/438,749filed Feb. 21, 2017, and titled “Voice Control of a Media PlaybackSystem,” which is herein incorporated by reference in its entirety.

Where the stream of sound data is sent to the VAS 190, upon receivingthe stream of sound data, the VAS 190 determines if there is voice inputin the streamed data from the NMD, and if so the VAS 190 will alsodetermine an underlying intent in the voice input. The VAS 190 may nexttransmit a response back to the MPS 100, which can include transmittingthe response directly to the NMD that caused the wake-word event. Theresponse is typically based on the intent that the VAS 190 determinedwas present in the voice input. As an example, in response to the VAS190 receiving a voice input with an utterance to “Play Hey Jude by TheBeatles,” the VAS 190 may determine that the underlying intent of thevoice input is to initiate playback and further determine that intent ofthe voice input is to play the particular song “Hey Jude.” After thesedeterminations, the VAS 190 may transmit a command to a particular MCS192 to retrieve content (i.e., the song “Hey Jude”), and that MCS 192,in turn, provides (e.g., streams) this content directly to the MPS 100or indirectly via the VAS 190. In some implementations, the VAS 190 maytransmit to the MPS 100 a command that causes the MPS 100 itself toretrieve the content from the MCS 192.

In another example, upon receiving an input data stream, the playbackdevice 102 or NMD 103 determines if there is voice input in the datastream and if so, also determines an underlying intent in the voiceinput. As an example, in response to receiving a voice input with anutterance to “Play Hey Jude by The Beatles,” the playback device 102 orthe NMD 103 may determine that the underlying intent of the voice inputis to initiate playback and further determine that intent of the voiceinput is to play the particular media item “Hey Jude.” After thesedeterminations, the content corresponding to the particular item isretrieved from data storage associated with the media playback system orfrom another content source, such as a media streaming service.

In certain implementations, NMDs may facilitate arbitration amongst oneanother when voice input is identified in speech detected by two or moreNMDs located within proximity of one another. For example, theNMD-equipped playback device 102 d in the environment 101 (FIG. 1A) isin relatively close proximity to the NMD-equipped Living Room playbackdevice 102 m, and both devices 102 d and 102 m may at least sometimesdetect the same sound. In such cases, this may require arbitration as towhich device is ultimately responsible for providing detected-sound datato the remote VAS. Examples of arbitrating between NMDs may be found,for example, in previously referenced U.S. application Ser. No.15/438,749.

In certain implementations, an NMD may be assigned to, or otherwiseassociated with, a designated or default playback device that may notinclude an NMD. For example, the Island NMD 103 f in the Kitchen 101 h(FIG. 1A) may be assigned to the Dining Room playback device 102 l,which is in relatively close proximity to the Island NMD 103 f. Inpractice, an NMD may direct an assigned playback device to play audio inresponse to a remote VAS receiving a voice input from the NMD to playthe audio, which the NMD might have sent to the VAS in response to auser speaking a command to play a certain song, album, playlist, etc.Additional details regarding assigning NMDs and playback devices asdesignated or default devices may be found, for example, in previouslyreferenced U.S. patent application No.

Further aspects relating to the different components of the example MPS100 and how the different components may interact to provide a user witha media experience may be found in the following sections. Whilediscussions herein may generally refer to the example MPS 100,technologies described herein are not limited to applications within,among other things, the home environment described above. For instance,the technologies described herein may be useful in other homeenvironment configurations comprising more or fewer of any of theplayback, network microphone, and/or controller devices 102-104. Forexample, the technologies herein may be utilized within an environmenthaving a single playback device 102 and/or a single NMD 103. In someexamples of such cases, the NETWORK 111 (FIG. 1B) may be eliminated andthe single playback device 102 and/or the single NMD 103 may communicatedirectly with the remote computing devices 106—d. In some embodiments, atelecommunication network (e.g., an LTE network, a 5G network, etc.) maycommunicate with the various playback, network microphone, and/orcontroller devices 102-104 independent of a LAN.

a. Example Playback & Network Microphone Devices

FIG. 2A is a functional block diagram illustrating certain aspects ofone of the playback devices 102 of the MPS 100 of FIGS. 1A and 1B. Asshown, the playback device 102 includes various components, each ofwhich is discussed in further detail below, and the various componentsof the playback device 102 may be operably coupled to one another via asystem bus, communication network, or some other connection mechanism.In the illustrated example of FIG. 2A, the playback device 102 may bereferred to as an “NMD-equipped” playback device because it includescomponents that support the functionality of an NMD, such as one of theNMDs 103 shown in FIG. 1A.

As shown, the playback device 102 includes at least one processor 212,which may be a clock-driven computing component configured to processinput data according to instructions stored in memory 213. The memory213 may be a tangible, non-transitory, computer-readable mediumconfigured to store instructions that are executable by the processor212. For example, the memory 213 may be data storage that can be loadedwith software code 214 that is executable by the processor 212 toachieve certain functions.

In one example, these functions may involve the playback device 102retrieving audio data from an audio source, which may be anotherplayback device. In another example, the functions may involve theplayback device 102 sending audio data, detected-sound data (e.g.,corresponding to a voice input), and/or other information to anotherdevice on a network via at least one network interface 224. In yetanother example, the functions may involve the playback device 102causing one or more other playback devices to synchronously playbackaudio with the playback device 102. In yet a further example, thefunctions may involve the playback device 102 facilitating being pairedor otherwise bonded with one or more other playback devices to create amulti-channel audio environment. Numerous other example functions arepossible, some of which are discussed below.

As just mentioned, certain functions may involve the playback device 102synchronizing playback of audio content with one or more other playbackdevices. During synchronous playback, a listener may not perceivetime-delay differences between playback of the audio content by thesynchronized playback devices. U.S. Pat. No. 8,234,395 filed on Apr. 4,2004, and titled “System and method for synchronizing operations among aplurality of independently clocked digital data processing devices,”which is hereby incorporated by reference in its entirety, provides inmore detail some examples for audio playback synchronization amongplayback devices.

To facilitate audio playback, the playback device 102 includes audioprocessing components 216 that are generally configured to process audioprior to the playback device 102 rendering the audio. In this respect,the audio processing components 216 may include one or moredigital-to-analog converters (“DAC”), one or more audio preprocessingcomponents, one or more audio enhancement components, one or moredigital signal processors (“DSPs”), and so on. In some implementations,one or more of the audio processing components 216 may be a subcomponentof the processor 212. In operation, the audio processing components 216receive analog and/or digital audio and process and/or otherwiseintentionally alter the audio to produce audio signals for playback.

The produced audio signals may then be provided to one or more audioamplifiers 217 for amplification and playback through one or morespeakers 218 operably coupled to the amplifiers 217. The audioamplifiers 217 may include components configured to amplify audiosignals to a level for driving one or more of the speakers 218.

Each of the speakers 218 may include an individual transducer (e.g., a“driver”) or the speakers 218 may include a complete speaker systeminvolving an enclosure with one or more drivers. A particular driver ofa speaker 218 may include, for example, a subwoofer (e.g., for lowfrequencies), a mid-range driver (e.g., for middle frequencies), and/ora tweeter (e.g., for high frequencies). In some cases, a transducer maybe driven by an individual corresponding audio amplifier of the audioamplifiers 217. In some implementations, a playback device may notinclude the speakers 218, but instead may include a speaker interfacefor connecting the playback device to external speakers. In certainembodiments, a playback device may include neither the speakers 218 northe audio amplifiers 217, but instead may include an audio interface(not shown) for connecting the playback device to an external audioamplifier or audio-visual receiver.

In addition to producing audio signals for playback by the playbackdevice 102, the audio processing components 216 may be configured toprocess audio to be sent to one or more other playback devices, via thenetwork interface 224, for playback. In example scenarios, audio contentto be processed and/or played back by the playback device 102 may bereceived from an external source, such as via an audio line-in interface(e.g., an auto-detecting 3.5 mm audio line-in connection) of theplayback device 102 (not shown) or via the network interface 224, asdescribed below.

As shown, the at least one network interface 224, may take the form ofone or more wireless interfaces 225 and/or one or more wired interfaces226. A wireless interface may provide network interface functions forthe playback device 102 to wirelessly communicate with other devices(e.g., other playback device(s), NMD(s), and/or controller device(s)) inaccordance with a communication protocol (e.g., any wireless standardincluding IEEE 802.11a, 802.11b, 802.11g, 802.11n, 802.11ac, 802.15, 4Gmobile communication standard, and so on). A wired interface may providenetwork interface functions for the playback device 102 to communicateover a wired connection with other devices in accordance with acommunication protocol (e.g., IEEE 802.3). While the network interface224 shown in FIG. 2A include both wired and wireless interfaces, theplayback device 102 may in some implementations include only wirelessinterface(s) or only wired interface(s).

In general, the network interface 224 facilitates data flow between theplayback device 102 and one or more other devices on a data network. Forinstance, the playback device 102 may be configured to receive audiocontent over the data network from one or more other playback devices,network devices within a LAN, and/or audio content sources over a WAN,such as the Internet. In one example, the audio content and othersignals transmitted and received by the playback device 102 may betransmitted in the form of digital packet data comprising an InternetProtocol (IP)-based source address and IP-based destination addresses.In such a case, the network interface 224 may be configured to parse thedigital packet data such that the data destined for the playback device102 is properly received and processed by the playback device 102.

As shown in FIG. 2A, the playback device 102 also includes voiceprocessing components 220 that are operably coupled to one or moremicrophones 222. The microphones 222 are configured to detect sound(i.e., acoustic waves) in the environment of the playback device 102,which is then provided to the voice processing components 220. Morespecifically, each microphone 222 is configured to detect sound andconvert the sound into a digital or analog signal representative of thedetected sound, which can then cause the voice processing component 220to perform various functions based on the detected sound, as describedin greater detail below. In one implementation, the microphones 222 arearranged as an array of microphones (e.g., an array of six microphones).In some implementations, the playback device 102 includes more than sixmicrophones (e.g., eight microphones or twelve microphones) or fewerthan six microphones (e.g., four microphones, two microphones, or asingle microphones).

In operation, the voice-processing components 220 are generallyconfigured to detect and process sound received via the microphones 222,identify potential voice input in the detected sound, and extractdetected-sound data to enable a VAS, such as the VAS 190 (FIG. 1B), toprocess voice input identified in the detected-sound data. The voiceprocessing components 220 may include one or more analog-to-digitalconverters, an acoustic echo canceller (“AEC”), a spatial processor(e.g., one or more multi-channel Wiener filters, one or more otherfilters, and/or one or more beam former components), one or more buffers(e.g., one or more circular buffers), one or more wake-word engines, oneor more voice extractors, and/or one or more speech processingcomponents (e.g., components configured to recognize a voice of aparticular user or a particular set of users associated with ahousehold), among other example voice processing components. In exampleimplementations, the voice processing components 220 may include orotherwise take the form of one or more DSPs or one or more modules of aDSP. In this respect, certain voice processing components 220 may beconfigured with particular parameters (e.g., gain and/or spectralparameters) that may be modified or otherwise tuned to achieveparticular functions. In some implementations, one or more of the voiceprocessing components 220 may be a subcomponent of the processor 212.

As further shown in FIG. 2A, the playback device 102 also includes powercomponents 227. The power components 227 include at least an externalpower source interface 228, which may be coupled to a power source (notshown) via a power cable or the like that physically connects theplayback device 102 to an electrical outlet or some other external powersource. Other power components may include, for example, transformers,converters, and like components configured to format electrical power.

In some implementations, the power components 227 of the playback device102 may additionally include an internal power source 229 (e.g., one ormore batteries) configured to power the playback device 102 without aphysical connection to an external power source. When equipped with theinternal power source 229, the playback device 102 may operateindependent of an external power source. In some such implementations,the external power source interface 228 may be configured to facilitatecharging the internal power source 229. As discussed before, a playbackdevice comprising an internal power source may be referred to herein asa “portable playback device.” On the other hand, a playback device thatoperates using an external power source may be referred to herein as a“stationary playback device,” although such a device may in fact bemoved around a home or other environment.

The playback device 102 further includes a user interface 240 that mayfacilitate user interactions independent of or in conjunction with userinteractions facilitated by one or more of the controller devices 104.In various embodiments, the user interface 240 includes one or morephysical buttons and/or supports graphical interfaces provided on touchsensitive screen(s) and/or surface(s), among other possibilities, for auser to directly provide input. The user interface 240 may furtherinclude one or more of lights (e.g., LEDs) and the speakers to providevisual and/or audio feedback to a user.

As an illustrative example, FIG. 2B shows an example housing 230 of theplayback device 102 that includes a user interface in the form of acontrol area 232 at a top portion 234 of the housing 230. The controlarea 232 includes buttons 236 a-c for controlling audio playback, volumelevel, and other functions. The control area 232 also includes a button236 d for toggling the microphones 222 to either an on state or an offstate.

As further shown in FIG. 2B, the control area 232 is at least partiallysurrounded by apertures formed in the top portion 234 of the housing 230through which the microphones 222 (not visible in FIG. 2B) receive thesound in the environment of the playback device 102. The microphones 222may be arranged in various positions along and/or within the top portion234 or other areas of the housing 230 so as to detect sound from one ormore directions relative to the playback device 102.

By way of illustration, SONOS, Inc. presently offers (or has offered)for sale certain playback devices that may implement certain of theembodiments disclosed herein, including a “PLAY:1,” “PLAY:3,” “PLAY:5,”“PLAYBAR,” “CONNECT:AMP,” “PLAYBASE,” “BEAM,” “CONNECT,” and “SUB.” Anyother past, present, and/or future playback devices may additionally oralternatively be used to implement the playback devices of exampleembodiments disclosed herein. Additionally, it should be understood thata playback device is not limited to the examples illustrated in FIG. 2Aor 2B or to the SONOS product offerings. For example, a playback devicemay include, or otherwise take the form of, a wired or wirelessheadphone set, which may operate as a part of the MPS 100 via a networkinterface or the like. In another example, a playback device may includeor interact with a docking station for personal mobile media playbackdevices. In yet another example, a playback device may be integral toanother device or component such as a television, a lighting fixture, orsome other device for indoor or outdoor use.

FIG. 2C is a diagram of an example voice input 280 that may be processedby an NMD or an NMD-equipped playback device. The voice input 280 mayinclude a keyword portion 280 a and an utterance portion 280 b. Thekeyword portion 280 a may include a wake word or a command keyword. Inthe case of a wake word, the keyword portion 280 a corresponds todetected sound that caused a wake-word. The utterance portion 280 bcorresponds to detected sound that potentially comprises a user requestfollowing the keyword portion 280 a. An utterance portion 280 b can beprocessed to identify the presence of any words in detected-sound databy the NMD in response to the event caused by the keyword portion 280 a.In other examples, an utterance portion 208 b is processed to identifythe presence of any words in detected sound data by the NMD during agiven time period associated with a change in the state of the mediaplayback system without first identifying a keyword portion. In variousimplementations, an underlying intent can be determined based on thewords in the utterance portion 280 b. In certain implementations, anunderlying intent can also be based or at least partially based oncertain words in the keyword portion 280 a, such as when keyword portionincludes a command keyword. In any case, the words may correspond to oneor more commands, as well as a certain command and certain keywords. Akeyword in the voice utterance portion 280 b may be, for example, a wordidentifying a particular device or group in the MPS 100. For instance,in the illustrated example, the keywords in the voice utterance portion280 b may be one or more words identifying one or more zones in whichthe music is to be played, such as the Living Room and the Dining Room(FIG. 1A). In some cases, the utterance portion 280 b may includeadditional information, such as detected pauses (e.g., periods ofnon-speech) between words spoken by a user, as shown in FIG. 2C. Thepauses may demarcate the locations of separate commands, keywords, orother information spoke by the user within the utterance portion 280 b.

Based on certain command criteria, the NMD and/or a remote VAS may takeactions as a result of identifying one or more commands in the voiceinput. Command criteria may be based on the inclusion of certainkeywords within the voice input, among other possibilities.Additionally, or alternatively, command criteria for commands mayinvolve identification of one or more control-state and/or zone-statevariables in conjunction with identification of one or more particularcommands. Control-state variables may include, for example, indicatorsidentifying a level of volume, a queue associated with one or moredevices, and playback state, such as whether devices are playing aqueue, paused, etc. Zone-state variables may include, for example,indicators identifying which, if any, zone players are grouped.

In some implementations, the MPS 100 is configured to temporarily reducethe volume of audio content that it is playing upon detecting a certainkeyword, such as a wake word, in the keyword portion 280 a. The MPS 100may restore the volume after processing the voice input 280. Such aprocess can be referred to as ducking, examples of which are disclosedin U.S. patent application Ser. No. 15/438,749, incorporated byreference herein in its entirety.

FIG. 2D shows an example sound specimen. In this example, the soundspecimen corresponds to the sound-data stream (e.g., one or more audioframes) associated with a spotted wake word or command keyword in thekeyword portion 280 a of FIG. 2C. As illustrated, the example soundspecimen comprises sound detected in an NMD's environment (i)immediately before a wake or command word was spoken, which may bereferred to as a pre-roll portion (between times to and t₁), (ii) whilea wake or command word was spoken, which may be referred to as awake-meter portion (between times t₁ and t₂), and/or (iii) after thewake or command word was spoken, which may be referred to as a post-rollportion (between times t₂ and t₃). Other sound specimens are alsopossible. In various implementations, aspects of the sound specimen canbe evaluated according to an acoustic model which aims to mapmels/spectral features to phonemes in a given language model for furtherprocessing. For example, automatic speech recognition (ASR) may includesuch mapping for command-keyword detection. Wake-word detection engines,by contrast, may be precisely tuned to identify a specific wake-word,and a downstream action of invoking a VAS (e.g., by targeting only noncewords in the voice input processed by the playback device).

ASR for command keyword detection may be tuned to accommodate a widerange of keywords (e.g., 5, 10, 100, 1,000, 10,000 keywords). Commandkeyword detection, in contrast to wake-word detection, may involvefeeding ASR output to an onboard, local NLU which together with the ASRdetermine when command word events have occurred. In someimplementations described below, the local NLU may determine an intentbased on one or more other keywords in the ASR output produced by aparticular voice input. In these or other implementations, a playbackdevice may act on a detected command keyword event only when theplayback devices determine that certain conditions have been met, suchas environmental conditions (e.g., low background noise).

b. Example Playback Device Configurations

FIGS. 3A-3E show example configurations of playback devices. Referringfirst to FIG. 3A, in some example instances, a single playback devicemay belong to a zone. For example, the playback device 102 c (FIG. 1A)on the Patio may belong to Zone A. In some implementations describedbelow, multiple playback devices may be “bonded” to form a “bondedpair,” which together form a single zone. For example, the playbackdevice 102 f (FIG. 1A) named “Bed 1” in FIG. 3A may be bonded to theplayback device 102 g (FIG. 1A) named “Bed 2” in FIG. 3A to form Zone B.Bonded playback devices may have different playback responsibilities(e.g., channel responsibilities). In another implementation describedbelow, multiple playback devices may be merged to form a single zone.For example, the playback device 102 d named “Bookcase” may be mergedwith the playback device 102 m named “Living Room” to form a single ZoneC. The merged playback devices 102 d and 102 m may not be specificallyassigned different playback responsibilities. That is, the mergedplayback devices 102 d and 102 m may, aside from playing audio contentin synchrony, each play audio content as they would if they were notmerged.

For purposes of control, each zone in the MPS 100 may be represented asa single user interface (“UI”) entity. For example, as displayed by thecontroller devices 104, Zone A may be provided as a single entity named“Portable,” Zone B may be provided as a single entity named “Stereo,”and Zone C may be provided as a single entity named “Living Room.”

In various embodiments, a zone may take on the name of one of theplayback devices belonging to the zone. For example, Zone C may take onthe name of the Living Room device 102 m (as shown). In another example,Zone C may instead take on the name of the Bookcase device 102 d. In afurther example, Zone C may take on a name that is some combination ofthe Bookcase device 102 d and Living Room device 102 m. The name that ischosen may be selected by a user via inputs at a controller device 104.In some embodiments, a zone may be given a name that is different thanthe device(s) belonging to the zone. For example, Zone B in FIG. 3A isnamed “Stereo” but none of the devices in Zone B have this name. In oneaspect, Zone B is a single UI entity representing a single device named“Stereo,” composed of constituent devices “Bed 1” and “Bed 2.” In oneimplementation, the Bed 1 device may be playback device 102 f in themaster bedroom 101 h (FIG. 1A) and the Bed 2 device may be the playbackdevice 102 g also in the master bedroom 101 h (FIG. 1A).

As noted above, playback devices that are bonded may have differentplayback responsibilities, such as playback responsibilities for certainaudio channels. For example, as shown in FIG. 3B, the Bed 1 and Bed 2devices 102 f and 102 g may be bonded so as to produce or enhance astereo effect of audio content. In this example, the Bed 1 playbackdevice 102 f may be configured to play a left channel audio component,while the Bed 2 playback device 102 g may be configured to play a rightchannel audio component. In some implementations, such stereo bondingmay be referred to as “pairing.”

Additionally, playback devices that are configured to be bonded may haveadditional and/or different respective speaker drivers. As shown in FIG.3C, the playback device 102 b named “Front” may be bonded with theplayback device 102 k named “SUB.” The Front device 102 b may render arange of mid to high frequencies, and the SUB device 102 k may renderlow frequencies as, for example, a subwoofer. When unbonded, the Frontdevice 102 b may be configured to render a full range of frequencies. Asanother example, FIG. 3D shows the Front and SUB devices 102 b and 102 kfurther bonded with Right and Left playback devices 102 a and 102 j,respectively. In some implementations, the Right and Left devices 102 aand 102 j may form surround or “satellite” channels of a home theatersystem. The bonded playback devices 102 a, 102 b, 102 j, and 102 k mayform a single Zone D (FIG. 3A).

In some implementations, playback devices may also be “merged.” Incontrast to certain bonded playback devices, playback devices that aremerged may not have assigned playback responsibilities, but may eachrender the full range of audio content that each respective playbackdevice is capable of. Nevertheless, merged devices may be represented asa single UI entity (i.e., a zone, as discussed above). For instance,FIG. 3E shows the playback devices 102 d and 102 m in the Living Roommerged, which would result in these devices being represented by thesingle UI entity of Zone C. In one embodiment, the playback devices 102d and 102 m may playback audio in synchrony, during which each outputsthe full range of audio content that each respective playback device 102d and 102 m is capable of rendering.

In some embodiments, a stand-alone NMD may be in a zone by itself. Forexample, the NMD 103 h from FIG. 1A is named “Closet” and forms Zone Iin FIG. 3A. An NMD may also be bonded or merged with another device soas to form a zone. For example, the NMD device 103 f named “Island” maybe bonded with the playback device 102 i Kitchen, which together formZone F, which is also named “Kitchen.” Additional details regardingassigning NMDs and playback devices as designated or default devices maybe found, for example, in previously referenced U.S. patent applicationSer. No. 15/438,749. In some embodiments, a stand-alone NMD may not beassigned to a zone.

Zones of individual, bonded, and/or merged devices may be arranged toform a set of playback devices that playback audio in synchrony. Such aset of playback devices may be referred to as a “group,” “zone group,”“synchrony group,” or “playback group.” In response to inputs providedvia a controller device 104, playback devices may be dynamically groupedand ungrouped to form new or different groups that synchronously playback audio content. For example, referring to FIG. 3A, Zone A may begrouped with Zone B to form a zone group that includes the playbackdevices of the two zones. As another example, Zone A may be grouped withone or more other Zones C-I. The Zones A-I may be grouped and ungroupedin numerous ways. For example, three, four, five, or more (e.g., all) ofthe Zones A-I may be grouped. When grouped, the zones of individualand/or bonded playback devices may play back audio in synchrony with oneanother, as described in previously referenced U.S. Pat. No. 8,234,395.Grouped and bonded devices are example types of associations betweenportable and stationary playback devices that may be caused in responseto a trigger event, as discussed above and described in greater detailbelow.

In various implementations, the zones in an environment may be assigneda particular name, which may be the default name of a zone within a zonegroup or a combination of the names of the zones within a zone group,such as “Dining Room+Kitchen,” as shown in FIG. 3A. In some embodiments,a zone group may be given a unique name selected by a user, such as“Nick's Room,” as also shown in FIG. 3A. The name “Nick's Room” may be aname chosen by a user over a prior name for the zone group, such as theroom name “Master Bedroom.”

Referring back to FIG. 2A, certain data may be stored in the memory 213as one or more state variables that are periodically updated and used todescribe the state of a playback zone, the playback device(s), and/or azone group associated therewith. The memory 213 may also include thedata associated with the state of the other devices of the MPS 100,which may be shared from time to time among the devices so that one ormore of the devices have the most recent data associated with thesystem.

In some embodiments, the memory 213 of the playback device 102 may storeinstances of various variable types associated with the states.Variables instances may be stored with identifiers (e.g., tags)corresponding to type. For example, certain identifiers may be a firsttype “al” to identify playback device(s) of a zone, a second type “b1”to identify playback device(s) that may be bonded in the zone, and athird type “cl” to identify a zone group to which the zone may belong.As a related example, in FIG. 1A, identifiers associated with the Patiomay indicate that the Patio is the only playback device of a particularzone and not in a zone group. Identifiers associated with the LivingRoom may indicate that the Living Room is not grouped with other zonesbut includes bonded playback devices 102 a, 102 b, 102 j, and 102 k.Identifiers associated with the Dining Room may indicate that the DiningRoom is part of Dining Room+Kitchen group and that devices 103 f and 102i are bonded. Identifiers associated with the Kitchen may indicate thesame or similar information by virtue of the Kitchen being part of theDining Room+Kitchen zone group. Other example zone variables andidentifiers are described below.

In yet another example, the MPS 100 may include variables or identifiersrepresenting other associations of zones and zone groups, such asidentifiers associated with Areas, as shown in FIG. 3A. An Area mayinvolve a cluster of zone groups and/or zones not within a zone group.For instance, FIG. 3A shows a first area named “First Area” and a secondarea named “Second Area.” The First Area includes zones and zone groupsof the Patio, Den, Dining Room, Kitchen, and Bathroom. The Second Areaincludes zones and zone groups of the Bathroom, Nick's Room, Bedroom,and Living Room. In one aspect, an Area may be used to invoke a clusterof zone groups and/or zones that share one or more zones and/or zonegroups of another cluster. In this respect, such an Area differs from azone group, which does not share a zone with another zone group. Furtherexamples of techniques for implementing Areas may be found, for example,in U.S. application Ser. No. 15/682,506 filed Aug. 21, 2017 and titled“Room Association Based on Name,” and U.S. Pat. No. 8,483,853 filed Sep.11, 2007, and titled “Controlling and manipulating groupings in amulti-zone media system.” Each of these applications is incorporatedherein by reference in its entirety. In some embodiments, the MPS 100may not implement Areas, in which case the system may not storevariables associated with Areas.

The memory 213 may be further configured to store other data. Such datamay pertain to audio sources accessible by the playback device 102 or aplayback queue that the playback device (or some other playbackdevice(s)) may be associated with. In embodiments described below, thememory 213 is configured to store a set of command data for selecting aparticular VAS when processing voice inputs. During operation, one ormore playback zones in the environment of FIG. 1A may each be playingdifferent audio content. For instance, the user may be grilling in thePatio zone and listening to hip hop music being played by the playbackdevice 102 c, while another user may be preparing food in the Kitchenzone and listening to classical music being played by the playbackdevice 102 i. In another example, a playback zone may play the sameaudio content in synchrony with another playback zone.

For instance, the user may be in the Office zone where the playbackdevice 102 n is playing the same hip-hop music that is being played byplayback device 102 c in the Patio zone. In such a case, playbackdevices 102 c and 102 n may be playing the hip-hop in synchrony suchthat the user may seamlessly (or at least substantially seamlessly)enjoy the audio content that is being played out-loud while movingbetween different playback zones. Synchronization among playback zonesmay be achieved in a manner similar to that of synchronization amongplayback devices, as described in previously referenced U.S. Pat. No.8,234,395.

As suggested above, the zone configurations of the MPS 100 may bedynamically modified. As such, the MPS 100 may support numerousconfigurations. For example, if a user physically moves one or moreplayback devices to or from a zone, the MPS 100 may be reconfigured toaccommodate the change(s). For instance, if the user physically movesthe playback device 102 c from the Patio zone to the Office zone, theOffice zone may now include both the playback devices 102 c and 102 n.In some cases, the user may pair or group the moved playback device 102c with the Office zone and/or rename the players in the Office zoneusing, for example, one of the controller devices 104 and/or voiceinput. As another example, if one or more playback devices 102 are movedto a particular space in the home environment that is not already aplayback zone, the moved playback device(s) may be renamed or associatedwith a playback zone for the particular space.

Further, different playback zones of the MPS 100 may be dynamicallycombined into zone groups or split up into individual playback zones.For example, the Dining Room zone and the Kitchen zone may be combinedinto a zone group for a dinner party such that playback devices 102 iand 102 l may render audio content in synchrony. As another example,bonded playback devices in the Den zone may be split into (i) atelevision zone and (ii) a separate listening zone. The television zonemay include the Front playback device 102 b. The listening zone mayinclude the Right, Left, and SUB playback devices 102 a, 102 j, and 102k, which may be grouped, paired, or merged, as described above.Splitting the Den zone in such a manner may allow one user to listen tomusic in the listening zone in one area of the living room space, andanother user to watch the television in another area of the living roomspace. In a related example, a user may utilize either of the NMD 103 aor 103 b (FIG. 1B) to control the Den zone before it is separated intothe television zone and the listening zone. Once separated, thelistening zone may be controlled, for example, by a user in the vicinityof the NMD 103 a, and the television zone may be controlled, forexample, by a user in the vicinity of the NMD 103 b. As described above,however, any of the NMDs 103 may be configured to control the variousplayback and other devices of the MPS 100.

c. Example Controller Devices

FIG. 4 is a functional block diagram illustrating certain aspects of aselected one of the controller devices 104 of the MPS 100 of FIG. 1A.Such controller devices may also be referred to herein as a “controldevice” or “controller.” The controller device shown in FIG. 4 mayinclude components that are generally similar to certain components ofthe network devices described above, such as a processor 412, memory 413storing program software 414, at least one network interface 424, andone or more microphones 422. In one example, a controller device may bea dedicated controller for the MPS 100. In another example, a controllerdevice may be a network device on which media playback system controllerapplication software may be installed, such as for example, an iPhone™,iPad™ or any other smart phone, tablet, or network device (e.g., anetworked computer such as a PC or Mac™).

The memory 413 of the controller device 104 may be configured to storecontroller application software and other data associated with the MPS100 and/or a user of the system 100. The memory 413 may be loaded withinstructions in software 414 that are executable by the processor 412 toachieve certain functions, such as facilitating user access, control,and/or configuration of the MPS 100. The controller device 104 isconfigured to communicate with other network devices via the networkinterface 424, which may take the form of a wireless interface, asdescribed above.

In one example, system information (e.g., such as a state variable) maybe communicated between the controller device 104 and other devices viathe network interface 424. For instance, the controller device 104 mayreceive playback zone and zone group configurations in the MPS 100 froma playback device, an NMD, or another network device. Likewise, thecontroller device 104 may transmit such system information to a playbackdevice or another network device via the network interface 424. In somecases, the other network device may be another controller device.

The controller device 104 may also communicate playback device controlcommands, such as volume control and audio playback control, to aplayback device via the network interface 424. As suggested above,changes to configurations of the MPS 100 may also be performed by a userusing the controller device 104. The configuration changes may includeadding/removing one or more playback devices to/from a zone,adding/removing one or more zones to/from a zone group, forming a bondedor merged player, separating one or more playback devices from a bondedor merged player, among others.

As shown in FIG. 4 , the controller device 104 also includes a userinterface 440 that is generally configured to facilitate user access andcontrol of the MPS 100. The user interface 440 may include atouch-screen display or other physical interface configured to providevarious graphical controller interfaces, such as the controllerinterfaces 540 a and 540 b shown in FIGS. 5A and 5B. Referring to FIGS.5A and 5B together, the controller interfaces 540 a and 540 b includes aplayback control region 542, a playback zone region 543, a playbackstatus region 544, a playback queue region 546, and a sources region548. The user interface as shown is just one example of an interfacethat may be provided on a network device, such as the controller deviceshown in FIG. 4 , and accessed by users to control a media playbacksystem, such as the MPS 100. Other user interfaces of varying formats,styles, and interactive sequences may alternatively be implemented onone or more network devices to provide comparable control access to amedia playback system.

The playback control region 542 (FIG. 5A) may include selectable icons(e.g., by way of touch or by using a cursor) that, when selected, causeplayback devices in a selected playback zone or zone group to play orpause, fast forward, rewind, skip to next, skip to previous, enter/exitshuffle mode, enter/exit repeat mode, enter/exit cross fade mode, etc.The playback control region 542 may also include selectable icons that,when selected, modify equalization settings and/or playback volume,among other possibilities.

The playback zone region 543 (FIG. 5B) may include representations ofplayback zones within the MPS 100. The playback zones regions 543 mayalso include a representation of zone groups, such as the DiningRoom+Kitchen zone group, as shown.

In some embodiments, the graphical representations of playback zones maybe selectable to bring up additional selectable icons to manage orconfigure the playback zones in the MPS 100, such as a creation ofbonded zones, creation of zone groups, separation of zone groups, andrenaming of zone groups, among other possibilities.

For example, as shown, a “group” icon may be provided within each of thegraphical representations of playback zones. The “group” icon providedwithin a graphical representation of a particular zone may be selectableto bring up options to select one or more other zones in the MPS 100 tobe grouped with the particular zone. Once grouped, playback devices inthe zones that have been grouped with the particular zone will beconfigured to play audio content in synchrony with the playbackdevice(s) in the particular zone. Analogously, a “group” icon may beprovided within a graphical representation of a zone group. In thiscase, the “group” icon may be selectable to bring up options to deselectone or more zones in the zone group to be removed from the zone group.Other interactions and implementations for grouping and ungrouping zonesvia a user interface are also possible. The representations of playbackzones in the playback zone region 543 (FIG. 5B) may be dynamicallyupdated as playback zone or zone group configurations are modified.

The playback status region 544 (FIG. 5A) may include graphicalrepresentations of audio content that is presently being played,previously played, or scheduled to play next in the selected playbackzone or zone group. The selected playback zone or zone group may bevisually distinguished on a controller interface, such as within theplayback zone region 543 and/or the playback status region 544. Thegraphical representations may include track title, artist name, albumname, album year, track length, and/or other relevant information thatmay be useful for the user to know when controlling the MPS 100 via acontroller interface.

The playback queue region 546 may include graphical representations ofaudio content in a playback queue associated with the selected playbackzone or zone group. In some embodiments, each playback zone or zonegroup may be associated with a playback queue comprising informationcorresponding to zero or more audio items for playback by the playbackzone or zone group. For instance, each audio item in the playback queuemay comprise a uniform resource identifier (URI), a uniform resourcelocator (URL), or some other identifier that may be used by a playbackdevice in the playback zone or zone group to find and/or retrieve theaudio item from a local audio content source or a networked audiocontent source, which may then be played back by the playback device.

In one example, a playlist may be added to a playback queue, in whichcase information corresponding to each audio item in the playlist may beadded to the playback queue. In another example, audio items in aplayback queue may be saved as a playlist. In a further example, aplayback queue may be empty, or populated but “not in use” when theplayback zone or zone group is playing continuously streamed audiocontent, such as Internet radio that may continue to play untilotherwise stopped, rather than discrete audio items that have playbackdurations. In an alternative embodiment, a playback queue can includeInternet radio and/or other streaming audio content items and be “inuse” when the playback zone or zone group is playing those items. Otherexamples are also possible.

When playback zones or zone groups are “grouped” or “ungrouped,”playback queues associated with the affected playback zones or zonegroups may be cleared or re-associated. For example, if a first playbackzone including a first playback queue is grouped with a second playbackzone including a second playback queue, the established zone group mayhave an associated playback queue that is initially empty, that containsaudio items from the first playback queue (such as if the secondplayback zone was added to the first playback zone), that contains audioitems from the second playback queue (such as if the first playback zonewas added to the second playback zone), or a combination of audio itemsfrom both the first and second playback queues. Subsequently, if theestablished zone group is ungrouped, the resulting first playback zonemay be re-associated with the previous first playback queue or may beassociated with a new playback queue that is empty or contains audioitems from the playback queue associated with the established zone groupbefore the established zone group was ungrouped. Similarly, theresulting second playback zone may be re-associated with the previoussecond playback queue or may be associated with a new playback queuethat is empty or contains audio items from the playback queue associatedwith the established zone group before the established zone group wasungrouped. Other examples are also possible.

With reference still to FIGS. 5A and 5B, the graphical representationsof audio content in the playback queue region 646 (FIG. 5A) may includetrack titles, artist names, track lengths, and/or other relevantinformation associated with the audio content in the playback queue. Inone example, graphical representations of audio content may beselectable to bring up additional selectable icons to manage and/ormanipulate the playback queue and/or audio content represented in theplayback queue. For instance, a represented audio content may be removedfrom the playback queue, moved to a different position within theplayback queue, or selected to be played immediately, or after anycurrently playing audio content, among other possibilities. A playbackqueue associated with a playback zone or zone group may be stored in amemory on one or more playback devices in the playback zone or zonegroup, on a playback device that is not in the playback zone or zonegroup, and/or some other designated device. Playback of such a playbackqueue may involve one or more playback devices playing back media itemsof the queue, perhaps in sequential or random order.

The sources region 548 may include graphical representations ofselectable audio content sources and/or selectable voice assistantsassociated with a corresponding VAS. The VASes may be selectivelyassigned. In some examples, multiple VASes, such as AMAZON's Alexa,MICROSOFT's Cortana, etc., may be invokable by the same NMD. In someembodiments, a user may assign a VAS exclusively to one or more NMDs.For example, a user may assign a first VAS to one or both of the NMDs102 a and 102 b in the Living Room shown in FIG. 1A, and a second VAS tothe NMD 103 f in the Kitchen. Other examples are possible.

d. Example Audio Content Sources

The audio sources in the sources region 548 may be audio content sourcesfrom which audio content may be retrieved and played by the selectedplayback zone or zone group. One or more playback devices in a zone orzone group may be configured to retrieve for playback audio content(e.g., according to a corresponding URI or URL for the audio content)from a variety of available audio content sources. In one example, audiocontent may be retrieved by a playback device directly from acorresponding audio content source (e.g., via a line-in connection). Inanother example, audio content may be provided to a playback device overa network via one or more other playback devices or network devices. Asdescribed in greater detail below, in some embodiments audio content maybe provided by one or more media content services.

Example audio content sources may include a memory of one or moreplayback devices in a media playback system such as the MPS 100 of FIG.1 , local music libraries on one or more network devices (e.g., acontroller device, a network-enabled personal computer, or anetworked-attached storage (“NAS”)), streaming audio services providingaudio content via the Internet (e.g., cloud-based music services), oraudio sources connected to the media playback system via a line-in inputconnection on a playback device or network device, among otherpossibilities.

In some embodiments, audio content sources may be added or removed froma media playback system such as the MPS 100 of FIG. 1A. In one example,an indexing of audio items may be performed whenever one or more audiocontent sources are added, removed, or updated. Indexing of audio itemsmay involve scanning for identifiable audio items in allfolders/directories shared over a network accessible by playback devicesin the media playback system and generating or updating an audio contentdatabase comprising metadata (e.g., title, artist, album, track length,among others) and other associated information, such as a URI or URL foreach identifiable audio item found. Other examples for managing andmaintaining audio content sources may also be possible.

FIG. 6 is a message flow diagram illustrating data exchanges betweendevices of the MPS 100. At step 650 a, the MPS 100 receives anindication of selected media content (e.g., one or more songs, albums,playlists, podcasts, videos, stations) via the control device 104. Theselected media content can comprise, for example, media items storedlocally on or more devices (e.g., the audio source 105 of FIG. 1C)connected to the media playback system and/or media items stored on oneor more media service servers (one or more of the remote computingdevices 106 of FIG. 1B). In response to receiving the indication of theselected media content, the control device 104 transmits a message 651 ato the playback device 102 (FIGS. 1A-1C) to add the selected mediacontent to a playback queue on the playback device 102.

At step 650 b, the playback device 102 receives the message 651 a andadds the selected media content to the playback queue for play back.

At step 650 c, the control device 104 receives input corresponding to acommand to play back the selected media content. In response toreceiving the input corresponding to the command to play back theselected media content, the control device 104 transmits a message 651 bto the playback device 102 causing the playback device 102 to play backthe selected media content. In response to receiving the message 651 b,the playback device 102 transmits a message 651 c to the computingdevice 106 requesting the selected media content. The computing device106, in response to receiving the message 651 c, transmits a message 651d comprising data (e.g., audio data, video data, a URL, a URI)corresponding to the requested media content.

At step 650 d, the playback device 102 receives the message 651 d withthe data corresponding to the requested media content and plays back theassociated media content.

At step 650 e, the playback device 102 optionally causes one or moreother devices to play back the selected media content. In one example,the playback device 102 is one of a bonded zone of two or more players(FIG. 1M). The playback device 102 can receive the selected mediacontent and transmit all or a portion of the media content to otherdevices in the bonded zone. In another example, the playback device 102is a coordinator of a group and is configured to transmit and receivetiming information from one or more other devices in the group. Theother one or more devices in the group can receive the selected mediacontent from the computing device 106, and begin playback of theselected media content in response to a message from the playback device102 such that all of the devices in the group play back the selectedmedia content in synchrony.

III. Example Command Keyword Eventing

FIGS. 7A and 7B are functional block diagrams showing aspects of an NMD703 a and an NMD 703 configured in accordance with embodiments of thedisclosure. The NMD 703 a and NMD 703 b are referred to collectively asthe NMD 703. The NMD 703 may be generally similar to the NMD 103 andinclude similar components. As described in more detail below, the NMD703 a (FIG. 7A) is configured to handle certain voice inputs locally,without necessarily transmitting data representing the voice input to avoice assistant service. However, the NMD 703 a is also configured toprocess other voice inputs using a voice assistant service. The NMD 703b (FIG. 7B) is configured to process voice inputs using a voiceassistant service and may have limited or no local NLU or commandkeyword detection.

Referring to FIG. 7A, the NMD 703 includes voice capture components(“VCC”) 760, a VAS wake-word engine 770 a, and a voice extractor 773.The VAS wake-word engine 770 a and the voice extractor 773 are operablycoupled to the VCC 760. The NMD 703 a further comprises a windowdetector 771 a operably coupled to the VCC 760. The VAS wake-word engine770 a may be omitted if the NMD 703 is arranged to process commandkeywords automatically during a time period associated with anindication of a track change of the NMD 702 without requiring theutterance of a VAS wake-word.

The NMD 703 further includes microphones 720 and the at least onenetwork interface 720 as described above and may also include othercomponents, such as audio amplifiers, a user interface, etc., which arenot shown in FIG. 7A for purposes of clarity. The microphones 720 of theNMD 703 a are configured to provide detected sound, S_(D), from theenvironment of the NMD 703 to the VCC 760. The detected sound S_(D) maytake the form of one or more analog or digital signals. In exampleimplementations, the detected sound S_(D) may be composed of a pluralitysignals associated with respective channels 762 that are fed to the VCC760.

Each channel 762 may correspond to a particular microphone 720. Forexample, an NMD having six microphones may have six correspondingchannels. Each channel of the detected sound S_(D) may bear certainsimilarities to the other channels but may differ in certain regards,which may be due to the position of the given channel's correspondingmicrophone relative to the microphones of other channels. For example,one or more of the channels of the detected sound S_(D) may have agreater signal to noise ratio (“SNR”) of speech to background noise thanother channels.

As further shown in FIG. 7A, the VCC 760 includes an AEC 763, a spatialprocessor 764, and one or more buffers 768. In operation, the AEC 763receives the detected sound S_(D) and filters or otherwise processes thesound to suppress echoes and/or to otherwise improve the quality of thedetected sound S_(D). That processed sound may then be passed to thespatial processor 764.

The spatial processor 764 is typically configured to analyze thedetected sound S_(D) and identify certain characteristics, such as asound's amplitude (e.g., decibel level), frequency spectrum,directionality, etc. In one respect, the spatial processor 764 may helpfilter or suppress ambient noise in the detected sound S_(D) frompotential user speech based on similarities and differences in theconstituent channels 762 of the detected sound S_(D), as discussedabove. As one possibility, the spatial processor 764 may monitor metricsthat distinguish speech from other sounds. Such metrics can include, forexample, energy within the speech band relative to background noise andentropy within the speech band—a measure of spectral structure—which istypically lower in speech than in most common background noise. In someimplementations, the spatial processor 764 may be configured todetermine a speech presence probability, examples of such functionalityare disclosed in U.S. patent application Ser. No. 15/984,073, filed May18, 2018, titled “Linear Filtering for Noise-Suppressed SpeechDetection,” which is incorporated herein by reference in its entirety.

In operation, the one or more buffers 768—one or more of which may bepart of or separate from the memory 213 (FIG. 2A)— capture datacorresponding to the detected sound S_(D). More specifically, the one ormore buffers 768 capture detected-sound data that was processed by theupstream AEC 764 and spatial processor 766.

The network interface 724 may then provide this information to a remoteserver that may be associated with the MPS 100. In one aspect, theinformation stored in the additional buffer 769 does not reveal thecontent of any speech but instead is indicative of certain uniquefeatures of the detected sound itself. In a related aspect, theinformation may be communicated between computing devices, such as thevarious computing devices of the MPS 100, without necessarilyimplicating privacy concerns. In practice, the MPS 100 can use thisinformation to adapt and fine-tune voice processing algorithms,including sensitivity tuning as discussed below. In some implementationsthe additional buffer may comprise or include functionality similar tolookback buffers disclosed, for example, in U.S. patent application Ser.No. 15/989,715, filed May 25, 2018, titled “Determining and Adapting toChanges in Microphone Performance of Playback Devices”; U.S. patentapplication Ser. No. 16/141,875, filed Sep. 25, 2018, titled “VoiceDetection Optimization Based on Selected Voice Assistant Service”; andU.S. patent application Ser. No. 16/138,111, filed Sep. 21, 2018, titled“Voice Detection Optimization Using Sound Metadata,” which areincorporated herein by reference in their entireties.

In any event, the detected-sound data forms a digital representation(i.e., sound-data stream), S_(DS), of the sound detected by themicrophones 720. In practice, the sound-data stream S_(DS) may take avariety of forms. As one possibility, the sound-data stream S_(DS) maybe composed of frames, each of which may include one or more soundsamples. The frames may be streamed (i.e., read out) from the one ormore buffers 768 for further processing by downstream components, suchas the VAS wake-word engines 770 and the voice extractor 773 of the NMD703.

In some implementations, at least one buffer 768 captures detected-sounddata utilizing a sliding window approach in which a given amount (i.e.,a given window) of the most recently captured detected-sound data isretained in the at least one buffer 768 while older detected-sound datais overwritten when it falls outside of the window. For example, atleast one buffer 768 may temporarily retain 20 frames of a soundspecimen at given time, discard the oldest frame after an expirationtime, and then capture a new frame, which is added to the 19 priorframes of the sound specimen.

In practice, when the sound-data stream S_(DS) is composed of frames,the frames may take a variety of forms having a variety ofcharacteristics. As one possibility, the frames may take the form ofaudio frames that have a certain resolution (e.g., 16 bits ofresolution), which may be based on a sampling rate (e.g., 44,100 Hz).Additionally, or alternatively, the frames may include informationcorresponding to a given sound specimen that the frames define, such asmetadata that indicates frequency response, power input level, SNR,microphone channel identification, and/or other information of the givensound specimen, among other examples. Thus, in some embodiments, a framemay include a portion of sound (e.g., one or more samples of a givensound specimen) and metadata regarding the portion of sound. In otherembodiments, a frame may only include a portion of sound (e.g., one ormore samples of a given sound specimen) or metadata regarding a portionof sound.

In any case, downstream components of the NMD 703 may process thesound-data stream S_(DS). For instance, the VAS wake-word engines 770are configured to apply one or more identification algorithms to thesound-data stream S_(DS) (e.g., streamed sound frames) to spot potentialwake words in the detected-sound S_(D). This process may be referred toas automatic speech recognition. The VAS wake-word engine 770 a andwindow detector 771 a apply different identification algorithmscorresponding to their respective wake words, and further generatedifferent events based on detecting a wake word in the detected-soundS_(D).

Example wake word detection algorithms accept audio as input and providean indication of whether a wake word is present in the audio. Manyfirst- and third-party wake word detection algorithms are known andcommercially available. For instance, operators of a voice service maymake their algorithm available for use in third-party devices.Alternatively, an algorithm may be trained to detect certain wake-words.

For instance, when the VAS wake-word engine 770 a detects a potentialVAS wake word, the VAS work-word engine 770 a provides an indication ofa “VAS wake-word event” (also referred to as a “VAS wake-word trigger”).In the illustrated example of FIG. 7A, the VAS wake-word engine 770 aoutputs a signal, S_(VW), that indicates the occurrence of a VASwake-word event to the voice extractor 773.

In multi-VAS implementations, the NMD 703 may include a VAS selector 774(shown in dashed lines) that is generally configured to directextraction by the voice extractor 773 and transmission of the sound-datastream S_(DS) to the appropriate VAS when a given wake-word isidentified by a particular wake-word engine (and a correspondingwake-word trigger), such as the VAS wake-word engine 770 a and at leastone additional VAS wake-word engine 770 b (shown in dashed lines). Insuch implementations, the NMD 703 may include multiple, different VASwake-word engines and/or voice extractors, each supported by arespective VAS.

Similar to the discussion above, each VAS wake-word engine 770 may beconfigured to receive as input the sound-data stream S_(DS) from the oneor more buffers 768 and apply identification algorithms to cause awake-word trigger for the appropriate VAS. Thus, as one example, the VASwake-word engine 770 a may be configured to identify the wake word“Alexa” and cause the NMD 703 a to invoke the AMAZON VAS when “Alexa” isspotted. As another example, the wake-word engine 770 b may beconfigured to identify the wake word “Ok, Google” and cause the NMD 520to invoke the GOOGLE VAS when “Ok, Google” is spotted. In single-VASimplementations, the VAS selector 774 may be omitted.

In response to the VAS wake-word event (e.g., in response to the signalS_(VW) indicating the wake-word event), the voice extractor 773 isconfigured to receive and format (e.g., packetize) the sound-data streamS_(DS). For instance, the voice extractor 773 packetizes the frames ofthe sound-data stream S_(DS) into messages. The voice extractor 773transmits or streams these messages, M_(V), that may contain voice inputin real time or near real time to a remote VAS via the network interface724.

The VAS is configured to process the sound-data stream S_(DS) containedin the messages M_(V) sent from the NMD 703. More specifically, the NMD703 a is configured to identify a voice input 780 based on thesound-data stream S_(DS). As described in connection with FIG. 2C, thevoice input 780 may include a keyword portion and an utterance portion.The keyword portion corresponds to detected sound that caused awake-word event, or leads to a command-keyword event when one or morecertain conditions, such as certain playback conditions, are met. Forinstance, when the voice input 780 includes a VAS wake word, the keywordportion corresponds to detected sound that caused the wake-word engine770 a to output the wake-word event signal S_(VW) to the voice extractor773. The utterance portion in this case corresponds to detected soundthat potentially comprises a user request following the keyword portion.

When a VAS wake-word event occurs, the VAS may first process the keywordportion within the sound-data stream S_(DS) to verify the presence of aVAS wake word. In some instances, the VAS may determine that the keywordportion comprises a false wake word (e.g., the word “Election” when theword “Alexa” is the target VAS wake word). In such an occurrence, theVAS may send a response to the NMD 703 a with an instruction for the NMD703 a to cease extraction of sound data, which causes the voiceextractor 773 to cease further streaming of the detected-sound data tothe VAS. The VAS wake-word engine 770 a may resume or continuemonitoring sound specimens until it spots another potential VAS wakeword, leading to another VAS wake-word event. In some implementations,the VAS does not process or receive the keyword portion but insteadprocesses only the utterance portion.

In any case, the VAS processes the utterance portion to identify thepresence of any words in the detected-sound data and to determine anunderlying intent from these words. The words may correspond to one ormore commands, as well as certain keywords. The keyword may be, forexample, a word in the voice input identifying a particular device orgroup in the MPS 100. For instance, in the illustrated example, thekeyword may be one or more words identifying one or more zones in whichthe music is to be played, such as the Living Room and the Dining Room(FIG. 1A).

To determine the intent of the words, the VAS is typically incommunication with one or more databases associated with the VAS (notshown) and/or one or more databases (not shown) of the MPS 100. Suchdatabases may store various user data, analytics, catalogs, and otherinformation for natural language processing and/or other processing. Insome implementations, such databases may be updated for adaptivelearning and feedback for a neural network based on voice-inputprocessing. In some cases, the utterance portion may include additionalinformation, such as detected pauses (e.g., periods of non-speech)between words spoken by a user, as shown in FIG. 2C. The pauses maydemarcate the locations of separate commands, keywords, or otherinformation spoke by the user within the utterance portion.

After processing the voice input, the VAS may send a response to the MPS100 with an instruction to perform one or more actions based on anintent it determined from the voice input. For example, based on thevoice input, the VAS may direct the MPS 100 to initiate playback on oneor more of the playback devices 102, control one or more of theseplayback devices 102 (e.g., raise/lower volume, group/ungroup devices,etc.), or turn on/off certain smart devices, among other actions. Afterreceiving the response from the VAS, the wake-word engine 770 a of theNMD 703 may resume or continue to monitor the sound-data stream S_(DS1)until it spots another potential wake-word, as discussed above.

In general, the one or more identification algorithms that a particularVAS wake-word engine, such as the VAS wake-word engine 770 a, appliesare configured to analyze certain characteristics of the detected soundstream S_(DS) and compare those characteristics to correspondingcharacteristics of the particular VAS wake-word engine's one or moreparticular VAS wake words. For example, the wake-word engine 770 a mayapply one or more identification algorithms to spot spectralcharacteristics in the detected sound stream S_(DS) that match thespectral characteristics of the engine's one or more wake words, andthereby determine that the detected sound S_(D) comprises a voice inputincluding a particular VAS wake word.

In some implementations, the one or more identification algorithms maybe third-party identification algorithms (i.e., developed by a companyother than the company that provides the NMD 703 a). For instance,operators of a voice service (e.g., AMAZON) may make their respectivealgorithms (e.g., identification algorithms corresponding to AMAZON'sALEXA) available for use in third-party devices (e.g., the NMDs 103),which are then trained to identify one or more wake words for theparticular voice assistant service. Additionally, or alternatively, theone or more identification algorithms may be first-party identificationalgorithms that are developed and trained to identify certain wake wordsthat are not necessarily particular to a given voice service. Otherpossibilities also exist.

As noted above, the NMD 703 a also includes a window detector 771 awhich may operate in parallel with the VAS wake-word engine 770 a. Thewindow detector 771 a opens a detection window in which keywords can beidentified. The window detector 771 a may comprise two or more differentunits for determining whether a command keyword is comprised within thedetected sounds S_(D), such as the keyword engine 776 and the local NLU779. Like the VAS wake-word engine 770 a, each unit 776, 779 may applyone or more identification algorithms corresponding to one or morekeywords. A “keyword event” is generated when a particular keyword isidentified in the detected-sound S_(D). In contrast to the nonce wordstypically as utilized as VAS wake words, identified keywords function asboth the activation word and the command itself. For instance, examplekeywords may correspond to playback commands (e.g., “play,” “pause,”“skip,” etc.) as well as control commands (“turn on”, “turn off”, etc.),among other examples. Under appropriate conditions, based on detectingone of these command keywords, the NMD 703 a performs the correspondingcommand.

The window detector 771 a can employ an automatic speech recognizer 772.The ASR 772 is configured to output phonetic or phonemicrepresentations, such as text corresponding to words, based on sound inthe sound-data stream S_(DS) to text. For instance, the ASR 772 maytranscribe spoken words represented in the sound-data stream S_(DS) toone or more strings representing the voice input 780 as text. The windowdetector 771 may also comprise a local natural language unit (NLU) andkeyword engine 776 which may be arranged to receive the ASR output(labeled as S_(ASR)) and identify particular keywords as being keywordevents during the detection window, as described below.

In some examples, the keyword engine 776 may comprise a library ofkeywords and corresponding commands, such as “play”, “pause” and “skip”.The keyword engine 776 receives the ASR output S_(ASR) and analyzes theoutput S_(ASR) to identify whether a known command is comprised withinthe output S_(ASR), for example by performing a lookup within the listof keywords. If a known keyword is present within the output S_(ASR),then the keyword engine 776 generates a keyword event and initiates acommand corresponding to the command keyword.

As noted above, in some example implementations, the NMD 703 a isconfigured to perform natural language processing, which may be carriedout using an onboard natural language processor, referred to herein as anatural language unit (NLU) 779. The local NLU 779 is configured toanalyze text output of the ASR 772 of the window detector 771 a to spot(i.e., detect or identify) keywords in the voice input 780. In FIG. 7A,this output is illustrated as the signal S_(ASR).

In one aspect, the library of the local NLU 779 includes commandkeywords. When the local NLU 779 identifies a keyword in the signalS_(ASR), the window detector 771 a generates a keyword event andperforms a command corresponding to the keyword in the signal S_(ASR),assuming that one or more conditions corresponding to that keyword aresatisfied.

As with the keyword engine 776, the library of the local NLU 779 alsoinclude keywords corresponding to command, however, the library of thelocal NLU 779 may also comprise commands corresponding to parameters,enabling for more detailed inputs to be provided and more complexcommands to be performed. The local NLU 779 may then determine anunderlying intent from the matched keywords in the voice input 780. Forinstance, if the local NLU matches the keywords “David Bowie” and“kitchen” in combination with a play command, the local NLU 779 maydetermine an intent of playing David Bowie in the Kitchen 101 h on theplayback device 102 i. In contrast to a processing of the voice input780 by a cloud-based VAS, local processing of the voice input 780 by thelocal NLU 779 may be relatively less sophisticated, as the NLU 779 doesnot have access to the relatively greater processing capabilities andlarger voice databases that a VAS generally has access to.

In some examples, the local NLU 779 may determine an intent with one ormore slots, which correspond to respective keywords. For instance,referring back to the “play David Bowie in the Kitchen” example, whenprocessing the voice input, the local NLU 779 may determine that anintent is to play music (e.g., intent=playMusic), while a first slotincludes David Bowie as target content (e.g., slot1=DavidBowie) and asecond slot includes the Kitchen 101 h as the target playback device(e.g., slot2=kitchen). Here, the intent (to “playMusic”) is based on thecommand keyword and the slots are parameters modifying the intent to aparticular target content and playback device.

Determining whether to utilize the NLU 779 alone, to utilize the NLU 779in combination with the ASR 772, or to utilize the keyword engine 776may be dependent on one or more properties of the device or currentoperating environment. For example, where the device is a batterypowered device or is in a low-power mode, the device may default tousing the keyword engine 776 which requires less power.

Within examples, the window detector 771 a outputs a signal, S_(CW),that indicates the occurrence of a keyword event to the local NLU 779.In response to the command keyword event (e.g., in response to thesignal S_(CW) indicating the command keyword event), the local NLU 779is configured to receive and process the signal S_(ASR). In particular,the local NLU 779 looks at the words within the signal S_(ASR) to findkeywords that match keywords in the library of the local NLU 779.

Using a keyword engine comprising a library of known keywords andassociated commands, as described above, there is no requirement toprocess the output S_(ASR) using the local NLU 779 as will be describedbelow. This results in the performing of commands using fewer resourcesand results in a decrease in power which is especially beneficial forportable devices relying on battery power, since the use of the localNLU 779 can be power intensive in comparison to a keyword engineperforming a lookup in a library of keywords. Therefore, as shown inFIG. 7 b , the NMD 703 b may comprise only the command keyword engine776.

Some error in performing local automatic speech recognition is expected.Within examples, the ASR 772 may generate a confidence score whentranscribing spoken words to text, which indicates how closely thespoken words in the voice input 780 matches the sound patterns for thatword. In some implementations, generating a command keyword event isbased on the confidence score for a given command keyword. For instance,the window detector 771 a may generate a keyword event when theconfidence score for a given sound exceeds a given threshold value(e.g., 0.5 on a scale of 0-1, indicating that the given sound is morelikely than not the keyword). Conversely, when the confidence score fora given sound is at or below the given threshold value, the windowdetector 771 a does not generate the keyword event.

Similarly, some error in performing keyword matching is expected. Withinexamples, the local NLU may generate a confidence score when determiningan intent, which indicates how closely the transcribed words in thesignal S_(ASR) match the corresponding keywords in the library of thelocal NLU. In some implementations, performing an operation according toa determined intent is based on the confidence score for keywordsmatched in the signal S_(ASR). For instance, the NMD 703 may perform anoperation according to a determined intent when the confidence score fora given sound exceeds a given threshold value (e.g., 0.5 on a scale of0-1, indicating that the given sound is more likely than not the commandkeyword). Conversely, when the confidence score for a given intent is ator below the given threshold value, the NMD 703 does not perform theoperation according to the determined intent.

As noted above, in some implementations, a phrase may be used as acommand keyword, which provides additional syllables to match (or notmatch). For instance, the phrase “play me some music” has more syllablesthan “play,” which provides additional sound patterns to match to words.Accordingly, command keywords that are phrases may generally be lessprone to false wake words.

As indicated above, the NMD 703 a generates a command keyword event (andperforms a command corresponding to the detected command keyword) onlywhen certain conditions corresponding to a detected command keyword aremet. These conditions are intended to lower the prevalence of falsepositive command keyword events. For instance, after detecting thecommand keyword “skip,” the NMD 703 a generates a command keyword event(and skips to the next track) only when certain playback conditionsindicating that a skip should be performed are met. These playbackconditions may include, for example, (i) a first condition that a mediaitem is being played back, (ii) a second condition that a queue isactive, and (iii) a third condition that the queue includes a media itemsubsequent to the media item being played back. If any of theseconditions are not satisfied, the command keyword event is not generated(and no skip is performed).

The NMD 703 a includes the one or more state machine(s) 775 a tofacilitate determining whether the appropriate conditions are met. Thestate machine 775 a transitions between a first state and a second statebased on whether one or more conditions corresponding to the detectedcommand keyword are met. In particular, for a given command keywordcorresponding to a particular command requiring one or more particularconditions, the state machine 775 a transitions into a first state whenone or more particular conditions are satisfied and transitions into asecond state when at least one condition of the one or more particularconditions is not satisfied.

Within example implementations, the command conditions are based onstates indicated in state variables. As noted above, the devices of theMPS 100 may store state variables describing the state of the respectivedevice. For instance, the playback devices 102 may store state variablesindicating the state of the playback devices 102, such as the audiocontent currently playing (or paused), the volume levels, networkconnection status, and the like). These state variables are updated(e.g., periodically, or based on an event (i.e., when a state in a statevariable changes)) and the state variables further can be shared amongthe devices of the MPS 100, including the NMD 703.

Similarly, the NMD 703 may maintain these state variables (either byvirtue of being implemented in a playback device or as a stand-aloneNMD). The state machine 775 a monitors the states indicated in thesestate variables, and determines whether the states indicated in theappropriate state variables indicate that the command condition(s) aresatisfied. Based on these determinations, the state machine 775 atransitions between the first state and the second state, as describedabove.

In some implementations, the window detector 771 may be disabled unlesscertain conditions have been met via the state machines. For example,the first state and the second state of the state machine 775 a mayoperate as enable/disable toggles to the window detector 771 a. Inparticular, while a state machine 775 a is in the first state, the statemachine 775 a enables the window detector 771 a thereby opening an inputdetection window. Conversely, while the state machine 775 a is in thesecond state, the state machine 775 a disables the window detector 771 athereby disabling the input detection window and preventing voiceinputs. Accordingly, the disabled window detector 771 a ceases analyzingthe sound-data stream S_(DS). In such cases when at least one commandcondition is not satisfied, the NMD 703 a may suppress generation ofcommand keyword event when the window detector 771 a detects a commandkeyword. Suppressing generation may involve gating, blocking orotherwise preventing output from the window detector 771 a fromgenerating the keyword event. Alternatively, suppressing generation mayinvolve the NMD 703 ceasing to feed the sound-data stream S_(DS) to theASR 772. Such suppression prevents a command corresponding to thedetected command keyword from being performed when at least one commandcondition is not satisfied. In such embodiments, the window detector 771a may continue analyzing the sound-data stream S_(DS) while the statemachine 775 a is in the first state, but command keyword events aredisabled.

Other example conditions may be based on the output of a voice activitydetector (“VAD”) 765. The VAD 765 is configured to detect the presence(or lack thereof) of voice activity in the sound-data stream S_(DS). Inparticular, the VAD 765 may analyze frames corresponding to the pre-rollportion of the voice input 780 (FIG. 2D) with one or more voicedetection algorithms to determine whether voice activity was present inthe environment in certain time windows prior to a keyword portion ofthe voice input 780.

The VAD 765 may utilize any suitable voice activity detectionalgorithms. Example voice detection algorithms involve determiningwhether a given frame includes one or more features or qualities thatcorrespond to voice activity, and further determining whether thosefeatures or qualities diverge from noise to a given extent (e.g., if avalue exceeds a threshold for a given frame). Some example voicedetection algorithms involve filtering or otherwise reducing noise inthe frames prior to identifying the features or qualities.

In some examples, the VAD 765 may determine whether voice activity ispresent in the environment based on one or more metrics. For example,the VAD 765 can be configured to distinguish between frames that includevoice activity and frames that don't include voice activity. The framesthat the VAD determines have voice activity may be caused by speechregardless of whether it is near- or far-field. In this example andothers, the VAD 765 may determine a count of frames in the pre-rollportion of the voice input 780 that indicate voice activity. If thiscount exceeds a threshold percentage or number of frames, the VAD 765may be configured to output a signal or set a state variable indicatingthat voice activity is present in the environment. Other metrics may beused as well in addition to, or as an alternative to, such a count.

The presence of voice activity in an environment may indicate that avoice input is being directed to the NMD 73. Accordingly, when the VAD765 indicates that voice activity is not present in the environment(perhaps as indicated by a state variable set by the VAD 765) this maybe configured as one of the command conditions for the command keywords.When this condition is met (i.e., the VAD 765 indicates that voiceactivity is present in the environment), the state machine 775 a willtransition to the first state to enable performing commands based oncommand keywords, so long as any other conditions for a particularcommand keyword are satisfied. Further, in some implementations, the NMD703 may include a noise classifier 766. The noise classifier 766 isconfigured to determine sound metadata (frequency response, signallevels, etc.) and identify signatures in the sound metadatacorresponding to various noise sources. The noise classifier 766 mayinclude a neural network or other mathematical model configured toidentify different types of noise in detected sound data or metadata.One classification of noise may be speech (e.g., far-field speech).Another classification, may be a specific type of speech, such asbackground speech, and example of which is described in greater detailwith reference to FIG. 8 . Background speech may be differentiated fromother types of voice-like activity, such as more general voice activity(e.g., cadence, pauses, or other characteristics) of voice-like activitydetected by the VAD 765.

For example, analyzing the sound metadata can include comparing one ormore features of the sound metadata with known noise reference values ora sample population data with known noise. For example, any features ofthe sound metadata such as signal levels, frequency response spectra,etc. can be compared with noise reference values or values collected andaveraged over a sample population. In some examples, analyzing the soundmetadata includes projecting the frequency response spectrum onto aneigenspace corresponding to aggregated frequency response spectra from apopulation of NMDs. Further, projecting the frequency response spectrumonto an eigenspace can be performed as a pre-processing step tofacilitate downstream classification.

In various embodiments, any number of different techniques forclassification of noise using the sound metadata can be used, forexample machine learning using decision trees, or Bayesian classifiers,neural networks, or any other classification techniques. Alternativelyor additionally, various clustering techniques may be used, for exampleK-Means clustering, mean-shift clustering, expectation-maximizationclustering, or any other suitable clustering technique. Techniques toclassify noise may include one or more techniques disclosed in U.S.application Ser. No. 16/227,308 filed Dec. 20, 2018, and titled“Optimization of Network Microphone Devices Using Noise Classification,”which is herein incorporated by reference in its entirety.

Referring back to FIG. 7A, in some implementations, the additionalbuffer 769 (shown in dashed lines) may store information (e.g., metadataor the like) regarding the detected sound S_(D) that was processed bythe upstream AEC 763 and spatial processor 764. This additional buffer769 may be referred to as a “sound metadata buffer.” Examples of suchsound metadata include: (1) frequency response data, (2) echo returnloss enhancement measures, (3) voice direction measures; (4) arbitrationstatistics; and/or (5) speech spectral data. In example implementations,the noise classifier 766 may analyze the sound metadata in the buffer769 to classify noise in the detected sound S_(D).

As noted above, one classification of sound may be background speech,such as speech indicative of far-field speech and/or speech indicativeof a conversation not involving the NMD 703. The noise classifier 766may output a signal and/or set a state variable indicating thatbackground speech is present in the environment. The presence of voiceactivity (i.e., speech) in the pre-roll portion of the voice input 780indicates that the voice input 780 might not be directed to the NMD 703,but instead be conversational speech within the environment. Forinstance, a household member might speak something like “our kids shouldhave a play date soon” without intending to direct the command keyword“play” to the NMD 703.

Further, when the noise classifier indicates that background speech ispresent in the environment, this condition may disable the windowdetector 771 a. In some implementations, the condition of backgroundspeech being absent in the environment (perhaps as indicated by a statevariable set by the noise classifier 766) is configured as one of thecommand conditions for the command keywords. Accordingly, the statemachine 775 a will not transition to the first state when the noiseclassifier 766 indicates that background speech is present in theenvironment.

Further, the noise classifier 766 may determine whether backgroundspeech is present in the environment based on one or more metrics. Forexample, the noise classifier 766 may determine a count of frames in thepre-roll portion of the voice input 780 that indicate background speech.If this count exceeds a threshold percentage or number of frames, thenoise classifier 766 may be configured to output the signal or set thestate variable indicating that background speech is present in theenvironment. Other metrics may be used as well in addition to, or as analternative to, such a count.

Within example implementations, the NMD 703 a may support a plurality ofcommand keywords. To facilitate such support, the window detector 771 amay implement multiple identification algorithms corresponding torespective command keywords. Alternatively, the NMD 703 a may implementadditional window detectors 771 b configured to identify respectivecommand keywords. Yet further, the library of the local NLU 779 mayinclude a plurality of command keywords and be configured to search fortext patterns corresponding to these command keywords in the signalS_(ASR).

Further, command keywords may require different conditions. Forinstance, the conditions for “skip” may be different than the conditionsfor “play” as “skip” may require that the condition that a media item isbeing played back, and “play” may require the opposite condition that amedia item is not being played back. To facilitate these respectiveconditions, the NMD 703 a may implement respective state machines 775 acorresponding to each command keyword. Alternatively, the NMD 703 a mayimplement a state machine 775 a having respective states for eachcommand keyword. Other examples are possible as well.

In some example implementations, the VAS wake-word engine 770 agenerates a VAS wake-word event when certain conditions are met. The NMD703 b includes a state machine 775 b, which is similar to the statemachine 775 a. The state machine 775 b transitions between a first stateand a second state based on whether one or more conditions correspondingto the VAS wake word are met.

For instance, in some examples, the VAS wake-word engine 770 a maygenerate a VAS wake word event only when background speech was notpresent in the environment before a VAS wake-word event was detected. Anindication of whether voice activity is present in the environment maycome from the noise classifier 766. As noted above, the noise classifier766 may be configured to output a signal or set a state variableindicating that far-field speech is present in the environment. Yetfurther, the VAS wake-word engine 770 a may generate a VAS wake wordevent only when voice activity is present in the environment. Asindicated above, the VAD 765 may be configured to output a signal or seta state variable indicating that voice activity is present in theenvironment.

To illustrate, as shown in FIG. 7B, the VAS wake-word engine 770 a isconnected to the state machines 775 b. The state machine 775 b mayremain in a first state when one or more conditions are met, which mayinclude a condition of voice activity not being present in theenvironment. When the state machine 775 b is in the first state, the VASwake-word engine 770 a is enabled and will generate VAS wake-wordevents. If any of the one or more conditions are not met, the statemachine 775 b transitions to a second state, which disables the VASwake-word engine 770 a.

Yet further, the NMD 703 may include one or more sensors that output asignal indicating whether one or more users are in proximity to the NMD703. Example sensors include a temperature sensor, an infrared sensor,an imaging sensor, and/or a capacitive sensor, among other examples. TheNMD 703 may use output from such sensors to set one or more statevariables indicating whether one or more users are in proximity to theNMD 703. Then, the state machine 775 b may use the presence or lackthereof as a condition for the state machine 775 b. For instance, thestate machine 775 b may enable the VAS wake-word engine and/or thewindow detector 771 a when at least one user is in proximity to the NMD703.

To illustrate exemplary state machine operation, FIG. 7C is a blockdiagram illustrating the state machine 775 for an example commandkeyword requiring one or more command conditions. At 777 a, the statemachine 775 remains in the first state 778 a while all the commandconditions are satisfied. While the state machine 775 remains in thefirst state 778 a (and all command conditions are met), the NMD 703 awill generate a command keyword event when the command keyword isdetected by the window detector 771 a.

At 777 b, the state machine 775 transitions into the second state 778 bwhen any command condition is not satisfied. At 777 c, the state machine775 remains in the second state 778 b while any command condition is notsatisfied. While the state machine 775 remains in the second state 778b, the NMD 703 a will not act on the command keyword event when thecommand keyword is detected by the window detector 771 a.

Referring back to FIG. 7A, in some examples, the one or more additionalwindow detectors 771 b may include custom window detectors. Cloudservice providers, such as streaming audio services, may provide acustom keyword engine pre-configured with identification algorithmsconfigured to spot service-specific command keywords. Theseservice-specific command keywords may include commands for customservice features and/or custom names used in accessing the service.

For instance, the NMD 703 a may include a particular streaming audioservice (e.g., Apple Music) window detector 771 b. This particularwindow detector 771 b may be configured to detect command keywordsspecific to the particular streaming audio service and generatestreaming audio service wake word events. For instance, one commandkeyword may be “Friends Mix,” which corresponds to a command to playback a custom playlist generated from playback histories of one or more“friends” within the particular streaming audio service.

A custom window detector 771 b may be relatively more prone to falsewake words than the VAS wake-word engine 770 a, as generally, the VASwake-word engine 770 a is more sophisticated than a custom windowdetector 771 b. To mitigate this, custom command keywords may requireone or more conditions to be satisfied before generating a customcommand keyword event. Further, in some implementations, in an effort toreduce the prevalence of false positives, multiple conditions may beimposed as a requirement to include a custom window detector 771 b inthe NMD 703 a.

These custom command keyword conditions may include service-specificconditions. For instance, command keywords corresponding to premiumfeatures or playlists may require a subscription as a condition. Asanother example, custom command keywords corresponding to a particularstreaming audio service may require media items from that streamingaudio service in the playback queue. Other conditions are possible aswell.

To gate custom window detectors based on the custom command keywordconditions, the NMD 703 a may comprise additional state machines 775 acorresponding to each custom command keyword. Alternatively, the NMD 703a may implement a state machine 775 a having respective states for eachcustom command keyword. Other examples are possible as well. Thesecustom command conditions may depend on the state variables maintainedby the devices within the MPS 100, and may also depend on statevariables or other data structures representing a state of a useraccount of a cloud service, such as a streaming audio service.

A plurality of different keywords may be supported by the keyword engine776 of the window detector 771 a in the NMD. Furthermore, each keywordmay have a plurality of cognates having similar intent for use whenanalyzed by the NLU 779, such as:

-   -   ‘play’—‘turn on’, ‘resume’—be used to initiate the playback of a        media item, possibly in a playback queue;    -   ‘pause’— ‘stop’, ‘quiet’, ‘mute’, ‘off’— used to cease sound        emission by a playback device, for example by stopping playback        of a currently playing media item;    -   ‘next’— ‘skip’, ‘forward’, “skip forward”—used to go to a next        media item in a playback queue;    -   ‘previous’— ‘back’, ‘last’, “skip back”—used to go to a previous        media item in a playback queue;    -   ‘repeat’— ‘restart’, ‘again’— used to restart a currently        playing media item;    -   ‘shuffle’— ‘randomize’— used to play media items in a playback        queue in a random order;    -   ‘volume up’— ‘increase’, ‘turn up’, ‘louder’— used to increase a        playback volume; and    -   ‘volume down’— ‘decrease’, ‘turn down’, ‘quieter’— used to        decrease a playback volume.

A device state machine may also be used to monitor the overall state ofthe NMD 703 a. The keyword engine 776 and NLU 779 may be disabled untilthe device state machine indicates a track change has occurred or ispredicted to occur and then be enabled only for a given time period. Thedevice state machine may be used to generate the track changenotifications on the transition between the first state and secondstate, which in turn are detected by the window detector 771 a therebyenabling the keyword engine 776 and/or NLU 779 for a given period oftime. The device state machine can be used to indicate when a currenttrack is coming to an end such that the device is playing a currenttrack in a first state and upon the start of a next track the statemachine transitions to a second state. The individual states of thestate machine may be monitored to determine when a track change islikely. For example, the playback progress of a given media item can betracked such that it is determined when the media item is approachingthe end, the monitor may then raise a notification indicating that atrack change is predicted or imminent.

In some implementations, each of the keywords are associated with one ormore conditions based on the device state machine. For example, wherethere are no more media items in the playback queue, even if the commandkeyword ‘next’ was processed the command event would not be issued sincethe device is unable to play a next media item. Similarly, if the devicevolume was at a maximum volume, then an event associated with the‘volume up’ command would not be issued since the device is unable toincrease the volume further.

Referring back to FIG. 7A, in example embodiments, the VAS wake-wordengine 770 a and the window detector 771 a may take a variety of forms.For example, the VAS wake-word engine 770 a and the window detector 771a may take the form of one or more modules that are stored in memory ofthe NMD 703 a and/or the NMD 703 b (e.g., the memory 112 b of FIG. 1F).As another example, the VAS wake-word engine 770 a and the windowdetector 771 a may take the form of a general-purposes orspecial-purpose processor, or modules thereof. In this respect, multiplewake-word engines 770 and 771 may be part of the same component of theNMD 703 a or each wake-word engine 770 and 771 may take the form of acomponent that is dedicated for the particular wake-word engine. Otherpossibilities also exist.

To further reduce false positives, the window detector 771 a may utilizea relative low sensitivity compared with the VAS wake-word engine 770 a.In practice, a wake-word engine may include a sensitivity level settingthat is modifiable. The sensitivity level may define a degree ofsimilarity between a word identified in the detected sound streamS_(DS1) and the wake-word engine's one or more particular wake wordsthat is considered to be a match (i.e., that triggers a VAS wake-word orcommand keyword event). In other words, the sensitivity level defineshow closely, as one example, the spectral characteristics in thedetected sound stream S_(DS2) must match the spectral characteristics ofthe engine's one or more wake words to be a wake-word trigger.

In this respect, the sensitivity level generally controls how many falsepositives that the VAS wake-word engine 770 a and window detector 771 aidentifies. For example, if the VAS wake-word engine 770 a is configuredto identify the wake-word “Alexa” with a relatively high sensitivity,then false wake words of “Election” or “Lexus” may cause the wake-wordengine 770 a to flag the presence of the wake-word “Alexa.” In contrast,if the window detector 771 a is configured with a relatively lowsensitivity, then the false wake words of “may” or “day” would not causethe window detector 771 a to flag the presence of the command keyword“Play.”

In practice, a sensitivity level may take a variety of forms. In exampleimplementations, a sensitivity level takes the form of a confidencethreshold that defines a minimum confidence (i.e., probability) levelfor a wake-word engine that serves as a dividing line between triggeringor not triggering a wake-word event when the wake-word engine isanalyzing detected sound for its particular wake word. In this regard, ahigher sensitivity level corresponds to a lower confidence threshold(and more false positives), whereas a lower sensitivity levelcorresponds to a higher confidence threshold (and fewer falsepositives). For example, lowering a wake-word engine's confidencethreshold configures it to trigger a wake-word event when it identifieswords that have a lower likelihood that they are the actual particularwake word, whereas raising the confidence threshold configures theengine to trigger a wake-word event when it identifies words that have ahigher likelihood that they are the actual particular wake word. Withinexamples, a sensitivity level of the window detector 771 a may be basedon more or more confidence scores, such as the confidence score inspotting a command keyword and/or a confidence score in determining anintent. Other examples of sensitivity levels are also possible.

In example implementations, sensitivity level parameters (e.g., therange of sensitivities) for a particular wake-word engine can beupdated, which may occur in a variety of manners. As one possibility, aVAS or other third-party provider of a given wake-word engine mayprovide to the NMD 703 a wake-word engine update that modifies one ormore sensitivity level parameters for the given VAS wake-word engine 770a. By contrast, the sensitive level parameters of the window detector771 a may be configured by the manufacturer of the NMD 703 a or byanother cloud service (e.g., for a custom wake-word engine 771 b).

Notably, within certain examples, the NMD 703 a does not send any datarepresenting the detected sound S_(D) (e.g., the messages M_(V)) to aVAS when processing a voice input 780 including a command keyword. Inimplementations including the local NLU 779, the NMD 703 a can furtherprocess the voice utterance portion of the voice input 780 (in additionto the keyword word portion) without necessarily sending the voiceutterance portion of the voice input 780 to the VAS. Accordingly,speaking a voice input 780 (with a command keyword) to the NMD 703 mayprovide increased privacy relative to other NMDs that process all voiceinputs using a VAS. Furthermore, like keyword detection, in someexamples wake-word detection may only be active during an inputdetection window and inactive otherwise. This prevents the unintentionalactivation of the VAS during normal conversation because of thedetection of voice inputs which are similar to the VAS wake word, whichcan increase privacy.

As indicated above, the keywords in the library of the local NLU 779correspond to parameters. These parameters may define to perform thecommand corresponding to the detected command keyword. When keywords arerecognized in the voice input 780, the command corresponding to thedetected command keyword is performed according to parameterscorresponding to the detected keywords.

For instance, an example voice input 780 may be “play music at lowvolume” with “play” being the command keyword portion (corresponding toa playback command) and “music at low volume” being the voice utteranceportion. When analyzing this voice input 780, the NLU 779 may recognizethat “low volume” is a keyword in its library corresponding to aparameter representing a certain (low) volume level. Accordingly, theNLU 779 may determine an intent to play at this lower volume level.Then, when performing the playback command corresponding to “play,” thiscommand is performed according to the parameter representing a certainvolume level.

In a second example, another example voice input 780 may be “play myfavorites in the Kitchen” with “play” again being the command keywordportion (corresponding to a playback command) and “my favorites in theKitchen” as the voice utterance portion. When analyzing this voice input780, the NLU 779 may recognize that “favorites” and “Kitchen” matchkeywords in its library. In particular, “favorites” corresponds to afirst parameter representing particular audio content (i.e., aparticular playlist that includes a user's favorite audio tracks) while“Kitchen” corresponds to a second parameter representing a target forthe playback command (i.e., the kitchen 101 h zone. Accordingly, the NLU779 may determine an intent to play this particular playlist in thekitchen 101 h zone.

In a third example, a further example voice input 780 may be “volume up”with “volume” being the command keyword portion (corresponding to avolume adjustment command) and “up” being the voice utterance portion.When analyzing this voice input 780, the NLU 779 may recognize that “up”is a keyword in its library corresponding to a parameter representing acertain volume increase (e.g., a 10 point increase on a 100 point volumescale). Accordingly, the NLU 779 may determine an intent to increasevolume. Then, when performing the volume adjustment commandcorresponding to “volume,” this command is performed according to theparameter representing the certain volume increase.

Within examples, certain command keywords are functionally linked to asubset of the keywords within the library of the local NLU 779, whichmay hasten analysis. For instance, the command keyword “skip” may befunctionality linked to the keywords “forward” and “backward” and theircognates. Accordingly, when the command keyword “skip” is detected in agiven voice input 780, analyzing the voice utterance portion of thatvoice input 780 with the local NLU 779 may involve determining whetherthe voice input 780 includes any keywords that match these functionallylinked keywords (rather than determining whether the voice input 780includes any keywords that match any keyword in the library of the localNLU 779). Since vastly fewer keywords are checked, this analysis isrelatively quicker than a full search of the library. By contrast, anonce VAS wake word such as “Alexa” provides no indication as to thescope of the accompanying voice input.

Some commands may require one or more parameters, as such the commandkeyword alone does not provide enough information to perform thecorresponding command. For example, the command keyword “volume” mightrequire a parameter to specify a volume increase or decrease, as theintent of “volume” of volume alone is unclear. As another example, thecommand keyword “group” may require two or more parameters identifyingthe target devices to group.

Accordingly, in some example implementations, when a given commandkeyword is detected in the voice input 780 by the window detector 771 a,the local NLU 779 may determine whether the voice input 780 includeskeywords matching keywords in the library corresponding to the requiredparameters. If the voice input 780 does include keywords matching therequired parameters, the NMD 703 a proceeds to perform the command(corresponding to the given command keyword) according to the parametersspecified by the keywords.

However, if the voice input 780 does include keywords matching therequired parameters for the command, the NMD 703 a may prompt the userto provide the parameters. For instance, in a first example, the NMD 703a may play an audible prompt such as “I've heard a command, but I needmore information” or “Can I help you with something?” Alternatively, theNMD 703 a may send a prompt to a user's personal device via a controlapplication (e.g., the software components 132 c of the controldevice(s) 104).

In further examples, the NMD 703 a may play an audible prompt customizedto the detected command keyword. For instance, after detecting a commandkeyword corresponding to a volume adjustment command (e.g., “volume”),the audible prompt may include a more specific request such as “Do youwant to adjust the volume up or down?” As another example, for agrouping command corresponding to the command keyword “group,” theaudible prompt may be “Which devices do you want to group?” Supportingsuch specific audible prompts may be made practicable by supporting arelatively limited number of command keywords (e.g., less than 100), butother implementations may support more command keywords with thetrade-off of requiring additional memory and processing capability.

Within additional examples, when a voice utterance portion does notinclude keywords corresponding to one or more required parameters, theNMD 703 a may perform the corresponding command according to one or moredefault parameters. For instance, if a playback command does not includekeywords indicating target playback devices 102 for playback, the NMD703 a may default to playback on the NMD 703 a itself (e.g., if the NMD703 a is implemented within a playback device 102) or to playback on oneor more associated playback devices 102 (e.g., playback devices 102 inthe same room or zone as the NMD 703 a). Further, in some examples, theuser may configure default parameters using a graphical user interface(e.g., user interface 430) or voice user interface. For example, if agrouping command does not specify the playback devices 102 to group, theNMD 703 a may default to instructing two or more pre-configured defaultplayback devices 102 to form a synchrony group. Default parameters maybe stored in data storage (e.g., the memory 112 b (FIG. 1F)) andaccessed when the NMD 703 a determines that keywords exclude certainparameters. Other examples are possible as well.

In some cases, the NMD 703 a sends the voice input 780 to a VAS when thelocal NLU 779 is unable to process the voice input 780 (e.g., when thelocal NLU is unable to find matches to keywords in the library, or whenthe local NLU 779 has a low confidence score as to intent). In anexample, to trigger sending the voice input 780, the NMD 703 a maygenerate a bridging event, which causes the voice extractor 773 toprocess the sound-data stream S_(D), as discussed above. That is, theNMD 703 a generates a bridging event to trigger the voice extractor 773without a VAS wake-word being detected by the VAS wake-word engine 770 a(instead of based on a command keyword in the voice input 780, as wellas the NLU 779 being unable to process the voice input 780).

Before sending the voice input 780 to the VAS (e.g., via the messagesM_(V)), the NMD 703 a may obtain confirmation from the user that theuser acquiesces to the voice input 780 being sent to the VAS. Forinstance, the NMD 703 a may play an audible prompt to send the voiceinput to a default or otherwise configured VAS, such as “I'm sorry, Ididn't understand that. May I ask Alexa?” In another example, the NMD703 a may play an audible prompt using a VAS voice (i.e., a voice thatis known to most users as being associated with a particular VAS), suchas “Can I help you with something?” In such examples, generation of thebridging event (and trigging of the voice extractor 773) is contingenton a second affirmative voice input 780 from the user.

Within certain example implementations, the local NLU 779 may processthe signal S_(ASR) without necessarily a command keyword event beinggenerated by the window detector 771 a (i.e., directly). That is, theautomatic speech recognition 772 may be configured to perform automaticspeech recognition on the sound-data stream S_(D), which the local NLU779 processes for matching keywords without requiring a command keywordevent. If keywords in the voice input 780 are found to match keywordscorresponding to a command (possibly with one or more keywordscorresponding to one or more parameters), the NMD 703 a performs thecommand according to the one or more parameters.

Further, in such examples, the local NLU 779 may process the signalS_(ASR) directly only when certain conditions are met. In particular, insome embodiments, the local NLU 779 processes the signal S_(ASR) onlywhen the state machine 775 a is in the first state. The certainconditions may include a condition corresponding to no background speechin the environment. An indication of whether background speech ispresent in the environment may come from the noise classifier 766. Asnoted above, the noise classifier 766 may be configured to output asignal or set a state variable indicating that far-field speech ispresent in the environment. Further, another condition may correspond tovoice activity in the environment. The VAD 765 may be configured tooutput a signal or set a state variable indicating that voice activityis present in the environment. Similarly, the prevalence of falsepositive detection of commands with a direct processing approach may bemitigated using the conditions determined by the state machine 775 a.

In some examples, the library of the local NLU 779 is partiallycustomized to the individual user(s). In a first aspect, the library maybe customized to the devices that are within the household of the NMD(e.g., the household within the environment 101 (FIG. 1A)). Forinstance, the library of the local NLU may include keywordscorresponding to the names of the devices within the household, such asthe zone names of the playback devices 102 in the MPS 100. In a secondaspect, the library may be customized to the users of the devices withinthe household. For example, the library of the local NLU 779 may includekeywords corresponding to names or other identifiers of a user'spreferred playlists, artists, albums, and the like. Then, the user mayrefer to these names or identifiers when directing voice inputs to thewindow detector 771 a and the local NLU 779.

Within example implementations, the NMD 703 a may populate the libraryof the local NLU 779 locally within the network 111 (FIG. 1B). As notedabove, the NMD 703 a may maintain or have access to state variablesindicating the respective states of devices connected to the network 111(e.g., the playback devices 104). These state variables may includenames of the various devices. For instance, the kitchen 101 h mayinclude the playback device 101 b, which are assigned the zone name“Kitchen.” The NMD 703 a may read these names from the state variablesand include them in the library of the local NLU 779 by training thelocal NLU 779 to recognize them as keywords. The keyword entry for agiven name may then be associated with the corresponding device in anassociated parameter (e.g., by an identifier of the device, such as aMAC address or IP address). The NMD 703 a can then use the parameters tocustomize control commands and direct the commands to a particulardevice.

In further examples, the NMD 703 a may populate the library bydiscovering devices connected to the network 111. For instance, the NMD703 a may transmit discovery requests via the network 111 according to aprotocol configured for device discovery, such as universalplug-and-play (UPnP) or zero-configuration networking. Devices on thenetwork 111 may then respond to the discovery requests and exchange datarepresenting the device names, identifiers, addresses and the like tofacilitate communication and control via the network 111. The NMD 703 amay read these names from the exchanged messages and include them in thelibrary of the local NLU 779 by training the local NLU 779 to recognizethem as keywords.

IV. Example Input Detection Window Techniques

FIG. 8 is a flow diagram showing an example method 800 to perform aplayback command based on a keyword event which is received during aninput detection window. The method 800 may be performed by a device,such as the NMD 103 a of FIG. 1A or a playback device such as playbackdevice 102 of FIG. 2A. The device may include features of the NMD 103 aof FIG. 7A.

At block 802, the method 800 involves determining a track changeassociated with a playback queue. The indication may be representativeof an actual track change or a predicted track change and may be basedon a device state machine. For example, a track change which indicatesthe media playback system is to start playing a new media item may bedetermined as a media item approaches the end of its content, forexample within 20 seconds, 10 seconds, or 5 seconds from the end of themedia item. The indications may be associated with an output of aparticular NMD or playback device.

At block 804, an input detection window is opened for a given timeperiod. The input detection window enables an input sound data stream tobe received by the NMD 703 a. The input detection window is opened for agiven time period and starts at a predetermined time relative to a timeof the determined track change. For example, the input detection windowmay be opened 5 seconds before the end of a media item which is thedetermined track change. Further examples are described below withreference to FIGS. 9A-9D.

The given time period may be based on an analysis of historical datastored in data storage of the NMD 703 a. The historical data may includeprevious track changes and any associated commands associated with thosetrack changes, such as commands received by the system within apredetermined from the track change. In some examples, a frequency ofuse of the playback command and the amount of time between the issuanceof the playback command and a determined track change can be consideredwhen determining the length of the given time period. By analyzing thehistorical data, the time period can be customized based on previousinteractions with the NMD 703 a. Furthermore, it will be appreciatedthat the length of the time period can be adjusted based on preferencesset by a user, and individual users may have their own customized timeperiods associated with a user account of the media playback system.

At block 806, the method 800 involves receiving an input sound datastream detected by at least one microphone associated with the NMD 703 aduring the input detection window. The input sound data stream maycomprise a number of different commands and/or background noise asdescribed above in connection with FIG. 7A. By receiving the input sounddata stream during the input detection window, it enablesresource-intensive components of the NMD 703 a to be activated onlyduring the input detection window thereby increasing the efficiency ofthe system. It also prevents input sound data from being continuouslyprocessed, potentially increasing privacy and reducing false positives.

Next, at block 808, the method involves analyzing the input sound datastream to determine whether it comprises (i) a wake-word and/or (ii) acommand keyword. For example, the VAS wake word engine 770 a of the NMD703 a may apply one or more wake word identification algorithms to theinput sound data stream. Similarly, a keyword engine 776 and/or NLU 779of the window detector 771 a may monitor the input sound data stream forkeywords, perhaps using the ASR 772, as described above in connectionwith FIG. 7A. The keyword engine 776 may use the ASR 772 with a libraryof predetermined keywords and use pattern matching to undertake theanalysis, whereas the NLU 779 may use the ASR 772 along with one or moreneural networks to determine an intent of the input sound data stream.

The input sound data stream will be analyzed by the ASR 772 of thewindow detector 771 a when the input window is open, and the analysis ofthe input sound data stream may have an associated confidence value.When it is determined that the ASR 772 has a low confidence value in itsanalysis of the input sound data stream the NMD 703 a may transmit aportion of the input sound data stream to a remote server, such as aserver of a VAS. A low confidence value means that the output of the ASR772 maps to a keyword with low confidence, and as such may be indicativethat the input sound data stream contains keywords which are notcontained in a local library of the NMD 703 a. Where the input sounddata stream contains command keywords which are supported by the NMD 703a, at block 810 it is determined whether the input sound data streamcomprises a command keyword, such as those previously listed.

At block 812, a command, such as a command corresponding to the playbackcommand keyword is performed by the NMD 703 a. For example, a playbackcommand keyword ‘next’ may be detected in the input detection window,based on the analysis, a corresponding playback command is generated andperformed by the NMD 703 a causing the next media item in the mediaplayback queue to be played by the media playback system.

FIGS. 9A-9D are graphs 900, 910, 920, 930 of historical data indicatingthe receipt of commands either from a controller or via a voice input.The analysis of the historical data, as described above, may be used todetermine the time period in which the input detection window is opened.

FIG. 9A shows a graph 900 of the frequency of track change commandsreceived from a controller device associated with the media playbacksystem. Track change commands are those that cause a media playbackdevice to playback a different item than one currently playing. Thisincludes commands to navigate a playlist, such as “skip” and commands toedit a playlist, such as adding a track to “play next” using a userinterface of the controller device. The graph 900 shows the number ofcontroller change track commands received along the y-axis relative tothe time of a track along the x-axis, such that the frequency of changetrack commands over time 902 is represented by the dotted line. A timeof 0 on the x-axis is a media item or track boundary, for example wherea media item ends, the time along x-axis therefore indicates a frequencyof change track commands from Based on an analysis of the frequency overtime 902 the optimal length of time for the input detection window to beopened can be determined, as well as the optimal start time at which toopen the window.

Graph 900 is derived from real usage data and shows that there is asignificant peak of controller change track commands received around the10-second mark. It demonstrates that track change commands are morelikely to be received close to a media item boundary in a playlist. Assuch, it is desirable for the input detection window to be opened orstart around at that time. Events are also received before and afterthis peak, therefore it is also desirable to enable user interaction attimes other than a time corresponding to the peak frequency.Accordingly, the analysis of the historical data can be used to indicatethat a start 904 of the window and an end 906 of the window, or in someexamples a time period 908 from the start 904 of the window. In thisexample, the time period 908 is 18 seconds, the start 904 of the windowis 2 seconds after a media item boundary and the end 906 of the windowis 20 seconds after a media item boundary. The historical data may beassociated with a given user of the media playback system identified bya user account or login credentials. Consequently, the start of thewindow 904, the end of the window 906 or the time period 908 may bedependent on the given user's previous interaction with the mediaplayback system, or another media playback system.

In some examples, properties of the current playlist may be used todetermine the length of the input detection window. When a mediaplayback system is currently playing a last or final track of aplaylist, the input detection window activated at the end of the trackmay be modified, such as by extending the length of the window. Thisprovides the user with a longer time period to issue a command. Forexample, it may take a user longer to realize that nothing is playingthan for them to notice a track is playing which they which to skip.

FIG. 9B shows a graph 910 of volume change commands received from acontroller device associated with the media playback system. The graph910 shows the number of volume change commands received along the y-axisrelative to the time of a track along the x-axis, such that thefrequency of volume change commands over time 912 is represented by thedotted line. As with FIG. 9A, time=0 is a media item boundarycorresponding to a track change, and the beginning of a different mediaitem. Based on an analysis of the frequency over time 912, a length oftime for the input detection window to be opened can be determined, aswell as a start time at which to open the window.

Graph 910 is derived from real usage data and shows there is a peak ofcontroller change volume comments received around the 10-second mark,this may correspond to changes in mastering volume between tracks. Thedistribution of the commands is across a longer period of time than thetrack change commands in FIG. 9A and there is a higher frequency ofcommands ahead of the track change (media item boundary) at time=0.Accordingly, the analysis of the controller change volume commandsresults in a start 914 of the input detection window being moved tobefore the track change at time=0, as indicated by the position of thestart 914 of the window before zero on the x-axis. The end 906 of thewindow remains the same because the frequency of the change volumecommands received from the controller is minimal past the end of thewindow 906 already determined in accordance with Graph 900 of FIG. 9A.As a result, a time period 918 for keeping the input detection windowopen is extended.

FIG. 9C shows a graph 920 of voice events detected by a device, such asan NMD 703 a, associated with a media playback system. A voice eventhere is any utterance including at least one of a detected wake-word orcommand as discussed above with reference to FIG. 2C. The graph 920shows the number of voice events received along the y-axis relative tothe time of a track along the x-axis, with time=0 indicating a mediaitem boundary as for FIGS. 9A and 9B, such that the frequency of voiceevents over time 922 is represented by the hatched area. Based on ananalysis of the frequency over time 922, a length of time for the inputdetection window to be opened can be determined, as well as a start timeat which to open the window.

Graph 920 is created from real usage data and shows there is a largepeak of voice events received around the 5-second mark, and thedistribution of the events is across a shorter period than the trackchange commands of FIG. 9A and the volume commands of FIG. 9B. Itsuggests that voice events occur much closer to an track change, perhapsbecause a voice command can simply be spoken without first having tonavigate to the correct part of a user interface of a controller.Therefore, the analysis of the voice events results in a start 924 ofthe input detection window being positioned just after an track change(media item boundary), at around time=1 second and an end 926 of theinput detection window being positioned at around time=11 seconds. Assuch, a time period 928 for keeping the input detection window open isrelatively short at around 10 seconds, when compared to the analysisundertaken for controller track change commands and controller volumechange commands discussed above with reference to FIGS. 9A and 9B.

FIG. 9D shows a graph 930 of voice events received by a device, such asan NMD 703 a, associated with a media playback system. It depicts thesame data of a frequency of voice events over time as FIG. 9C and showshow an input window can be adjusted in start time, end time andduration. As shown schematically in FIG. 9D a predetermined start timet_(s) and a predetermined end time, t_(E), are predetermined, forexample set by a manufacturer of a device. t_(s) and t_(E) can bedetermined based on test data from a number of users, for example. Thiscan allow the voice input detection window to be used immediately, whenno actual usage data has been collected from the media playback systemitself. In use, as data indicating how the particular media playbacksystem is used is collected, the start time and end time may be adjustedbetween the limits AA and AB within a period 934 for the start time, andbetween the limits ΔC and ΔD within a period 936 for the end time. As aresult, the voice input window may vary between around 12 seconds inlength (depicted by input window 940) to around 25 seconds in length(depicted by input window 938).

Based on the range of the start and the end of the input detectionwindow, a user may specify a minimum and/or maximum time they wish theinput detection window to be open for, this can be used to override theanalyses undertaken, or may be used in combination with the analyses tofurther customize the length of time, as well as the start of the inputdetection window.

FIGS. 9A to 9D show how a voice input window which is open for a limitedtime based on an indication that a track change is or has occurred canpotentially improve privacy, reduce false positives and/or reduceresource usage. It can be seen that commands and voice events occur withhigher frequency around a media item boundary as an example, so thatopening an input window of finite duration associated with an indicationthat a track change has or is going to occur means that a highproportion of commands are still received.

In FIGS. 9A to 9D, the same track change is analyzed with reference toparticular types of commands from a controller application, in FIGS. 9Aand 9B, or voice events with reference to FIGS. 9C and 9D. The voiceinput window may be set based on any one of these analyses or by anycombination, for example by aggregating all commands received from acontroller and voice events.

In some examples, data of the relative timing of commands within awindow, such as the track commands of FIG. 9A and the volume commands ofFIG. 9B can be used to adjust a confidence score of an associatedcommand keywords.

CONCLUSION

The description above discloses, among other things, various examplesystems, methods, apparatus, and articles of manufacture including,among other components, firmware and/or software executed on hardware.It is understood that such examples are merely illustrative and shouldnot be considered as limiting. For example, it is contemplated that anyor all of the firmware, hardware, and/or software aspects or componentscan be embodied exclusively in hardware, exclusively in software,exclusively in firmware, or in any combination of hardware, software,and/or firmware. Accordingly, the examples provided are not the onlyway(s) to implement such systems, methods, apparatus, and/or articles ofmanufacture.

The specification is presented largely in terms of illustrativeenvironments, systems, procedures, steps, logic blocks, processing, andother symbolic representations that directly or indirectly resemble theoperations of data processing devices coupled to networks. These processdescriptions and representations are typically used by those skilled inthe art to most effectively convey the substance of their work to othersskilled in the art. Numerous specific details are set forth to provide athorough understanding of the present disclosure. However, it isunderstood to those skilled in the art that certain embodiments of thepresent disclosure can be practiced without certain, specific details.In other instances, well known methods, procedures, components, andcircuitry have not been described in detail to avoid unnecessarilyobscuring aspects of the embodiments. Accordingly, the scope of thepresent disclosure is defined by the appended claims rather than theforgoing description of embodiments.

When any of the appended claims are read to cover a purely softwareand/or firmware implementation, at least one of the elements in at leastone example is hereby expressly defined to include a tangible,non-transitory medium such as a memory, DVD, CD, Blu-ray, and so on,storing the software and/or firmware.

The invention claimed is:
 1. A playback device forming part of a mediaplayback system, the playback device comprising: at least one microphoneconfigured to detect sound; at least one processor; and data storagehaving instructions stored thereon that are executed by the at least oneprocessor to cause the playback device to perform operations comprising:detecting an event, the event being associated with the playback deviceor the media playback system comprising the playback device, wherein theevent is not based on sound data captured via the at least onemicrophone; responsive to the event detection, opening an inputdetection window for a given time period, and while the input detectionwindow is open: receiving, by the at least one processor, an input sounddata stream from the at least one microphone, wherein the input sounddata stream represents sound detected by the at least one microphone;analyzing the input sound data stream by the at least one processor fora plurality of command keywords supported by the playback device;determining, based on the analysis, that the input sound data streamincludes voice input data comprising a command keyword, wherein thecommand keyword is one of the plurality of command keywords supported bythe playback device; and responsive to the determining that the inputsound data stream includes voice input data comprising a commandkeyword, causing the media playback system to perform a commandcorresponding to the command keyword; and adjusting the given timeperiod associated with the input detection window over time.
 2. Theplayback device of claim 1, wherein adjusting the given time periodassociated with the input detection window over time is based on one ormore of: characteristics of a track change; a previous user interaction;preferences set by a user; or historical data including detected eventsand associated commands.
 3. The playback device according to claim 1,the operations further comprising storing historical data in the datastorage, the historical data including determined events and anyassociated commands, and wherein adjusting the given time periodcomprises analyzing the historical data to adjust the given time periodassociated with the input detection window.
 4. The playback deviceaccording to claim 1, wherein the given time period is associated with auser account of the media playback system.
 5. The playback deviceaccording to claim 1, wherein outside of the input detection window, theinput sound data stream is not analyzed.
 6. The playback deviceaccording to claim 1, further comprising: a network interface, and theinstructions stored on the data storage that are executed by the atleast one processor further cause the playback device to performfunctions comprising: transmitting, via the network interface and duringthe input detection window, at least part of the input sound data streamto a remote server for analysis; receiving data including a remotecommand from the remote server, the remote command being supported bythe playback device; and causing the media playback system to performthe remote command.
 7. The playback device according to claim 1, whereinthe analyzing the input sound data stream comprises determining acommand keyword by at least one of: natural language processing todetermine an intent, based on an analysis of the command keyword in theinput sound data stream; or pattern-matching based on a predefinedlibrary of keywords and associated command keywords.
 8. A method to beperformed by a playback device forming part of a media playback systemand comprising at least one microphone configured to detect sound, themethod comprising: detecting an event, the event being associated withthe playback device or the media playback system, wherein the event isnot based on sound data captured via the at least one microphone;responsive to the event detection, opening an input detection window fora given time period, and while the input detection window is open:receiving an input sound data stream from the at least one microphone,wherein the input sound data stream represents sound detected by the atleast one microphone; analyzing the input sound data stream for aplurality of command keywords supported by the playback device;determining, based on the analysis, that the input sound data streamincludes voice input data comprising a command keyword, wherein thecommand keyword is one of the plurality of command keywords supported bythe playback device; and responsive to the determining that the inputsound data stream includes voice input data comprising a commandkeyword, causing the media playback system to perform a commandcorresponding to the command keyword; and adjusting the given timeperiod associated with the input detection window over time.
 9. Themethod of claim 8, wherein adjusting the given time period associatedwith the input detection window over time is based on one or more of:characteristics of a track change; a previous user interaction;preferences set by a user; or historical data including detected eventsand associated commands.
 10. The method of claim 8, further comprisingstoring historical data in data storage, the historical data includingdetermined events and any associated commands, wherein adjusting thegiven time period comprises analyzing the historical data to adjust thegiven time period associated with the input detection window.
 11. Themethod of claim 8, wherein the given time period is associated with auser account of the media playback system.
 12. The method of claim 8,wherein outside of the input detection window, the input sound datastream is not analyzed.
 13. The method of claim 8, further comprising:transmitting, via a network interface of the playback device and duringthe input detection window, at least part of the input sound data streamto a remote server for analysis; receiving data including a remotecommand from the remote server, the remote command being supported bythe playback device; and causing the media playback system to performthe remote command.
 14. The method of claim 8, wherein the analyzing theinput sound data stream comprises determining a command keyword by atleast one of: natural language processing to determine an intent, basedon an analysis of the command keyword in the input sound data stream; orpattern-matching based on a predefined library of keywords andassociated command keywords.
 15. A non-transitory computer-readablemedium having instructions stored thereon that are executable by one ormore processors to cause a playback device to perform operations, theplayback device forming part of a media playback system and comprisingat least one microphone configured to detect sound, the operationscomprising: detecting an event, the event being associated with theplayback device or the media playback system, wherein the event is notbased on sound data captured via the at least one microphone; responsiveto the event detection, opening an input detection window for a giventime period, and while the input detection window is open: receiving aninput sound data stream from the at least one microphone, wherein theinput sound data stream represents sound detected by the at least onemicrophone; analyzing the input sound data stream for a plurality ofcommand keywords supported by the playback device; determining, based onthe analysis, that the input sound data stream includes voice input datacomprising a command keyword, wherein the command keyword is one of theplurality of command keywords supported by the playback device; andresponsive to the determining that the input sound data stream includesvoice input data comprising a command keyword, causing the mediaplayback system to perform a command corresponding to the commandkeyword; and adjusting the given time period associated with the inputdetection window over time.
 16. The computer-readable medium of claim15, wherein adjusting the given time period associated with the inputdetection window over time is based on one or more of: characteristicsof a track change; a previous user interaction; preferences set by auser; or historical data including detected events and associatedcommands.
 17. The computer-readable medium of claim 15, the operationsfurther comprising storing historical data in data storage, thehistorical data including determined events and any associated commands,wherein adjusting the given time period comprises analyzing thehistorical data to adjust the given time period associated with theinput detection window.
 18. The computer-readable medium of claim 15,wherein the given time period is associated with a user account of themedia playback system.
 19. The computer-readable medium of claim 15,wherein outside of the input detection window, the input sound datastream is not analyzed.
 20. The computer-readable medium of claim 15,the operations further comprising: transmitting, via a network interfaceof the playback device and during the input detection window, at leastpart of the input sound data stream to a remote server for analysis;receiving data including a remote command from the remote server, theremote command being supported by the playback device; and causing themedia playback system to perform the remote command.